SlideShare uma empresa Scribd logo
1 de 70
Baixar para ler offline
Boundary properties of factorial classes of graphs
Victor Zamaraev
Laboratory of Algorithms and Technologies for Networks Analysis (LATNA),
Higher School of Economics
Joint work with
Vadim Lozin, University of Warwick
Workshop on Extremal Graph Theory
6 June 2014
Boundary properties of factorial classes of graphs
Introduction
2 / 28
Boundary properties of factorial classes of graphs
Introduction
All considered graphs are simple (undirected, without loops and
without multiple edges).
3 / 28
Boundary properties of factorial classes of graphs
Introduction
All considered graphs are simple (undirected, without loops and
without multiple edges).
Graphs are labeled by natural numbers 1, . . . , n
6
4 5
1
2
3
3 / 28
Boundary properties of factorial classes of graphs
Introduction
Definition
A class is a set of graphs closed under isomorphism.
4 / 28
Boundary properties of factorial classes of graphs
Introduction
Definition
A class is a set of graphs closed under isomorphism.
Definition
A class of graphs is hereditary if it is closed under taking induced
subgraphs.
4 / 28
Boundary properties of factorial classes of graphs
Introduction
Definition
A class is a set of graphs closed under isomorphism.
Definition
A class of graphs is hereditary if it is closed under taking induced
subgraphs.
Exapmle
Let X be a hereditary class and W4 ∈ X. Then C4 ∈ X.
1
2
3 4
5 1
2 3
4
W4 C4 4 / 28
Boundary properties of factorial classes of graphs
Introduction
Every hereditary graph class X can be defined by a set of
forbidden induced subgraphs.
5 / 28
Boundary properties of factorial classes of graphs
Introduction
Every hereditary graph class X can be defined by a set of
forbidden induced subgraphs.
Let M be a set of graphs. Then Free(M) denotes the set of all
graphs not containing induced subgraphs isomorphic to graphs from
M.
5 / 28
Boundary properties of factorial classes of graphs
Introduction
Every hereditary graph class X can be defined by a set of
forbidden induced subgraphs.
Let M be a set of graphs. Then Free(M) denotes the set of all
graphs not containing induced subgraphs isomorphic to graphs from
M.
Statement
Class X is hereditary if and only if there exists M such that
X = Free(M).
We say that graphs in X are M-free.
5 / 28
Boundary properties of factorial classes of graphs
Introduction
Every hereditary graph class X can be defined by a set of
forbidden induced subgraphs.
Let M be a set of graphs. Then Free(M) denotes the set of all
graphs not containing induced subgraphs isomorphic to graphs from
M.
Statement
Class X is hereditary if and only if there exists M such that
X = Free(M).
We say that graphs in X are M-free.
Example
For the class of bipartite graphs M is {C3, C5, C7, . . . }, i.e.
B = Free(C3, C5, C7, . . . ). 5 / 28
Boundary properties of factorial classes of graphs
Introduction
For a class X denote by Xn the set of n-vertex graphs from X.
6 / 28
Boundary properties of factorial classes of graphs
Introduction
For a class X denote by Xn the set of n-vertex graphs from X.
Example
Let P be the class of all graph.
|Pn| = 2(n
2) = 2n(n−1)/2
6 / 28
Boundary properties of factorial classes of graphs
Introduction
For a class X denote by Xn the set of n-vertex graphs from X.
Example
Let P be the class of all graph.
|Pn| = 2(n
2) = 2n(n−1)/2
log2 |Pn| = Θ(n2)
6 / 28
Boundary properties of factorial classes of graphs
Introduction
Theorem (Alekseev V. E., 1992; Bollob´as B. and Thomason A., 1994)
For every infinite hereditary class X, which is not the class of all
graphs:
log2 |Xn| = 1 −
1
c(X)
n2
2
+ o(n2
), (1)
where c(X) ∈ N is the index of class X.
7 / 28
Boundary properties of factorial classes of graphs
Introduction
Theorem (Alekseev V. E., 1992; Bollob´as B. and Thomason A., 1994)
For every infinite hereditary class X, which is not the class of all
graphs:
log2 |Xn| = 1 −
1
c(X)
n2
2
+ o(n2
), (1)
where c(X) ∈ N is the index of class X.
(i) For c(X) > 1, log2 |Xn| = Θ(n2)
7 / 28
Boundary properties of factorial classes of graphs
Introduction
Theorem (Alekseev V. E., 1992; Bollob´as B. and Thomason A., 1994)
For every infinite hereditary class X, which is not the class of all
graphs:
log2 |Xn| = 1 −
1
c(X)
n2
2
+ o(n2
), (1)
where c(X) ∈ N is the index of class X.
(i) For c(X) > 1, log2 |Xn| = Θ(n2)
(ii) For c(X) = 1, log2 |Xn| = o(n2)
7 / 28
Boundary properties of factorial classes of graphs
Introduction
Let c(X) = 1
Question
What are possible rates of growth of a function log2 |Xn|?
8 / 28
Boundary properties of factorial classes of graphs
Introduction
Let c(X) = 1
Question
What are possible rates of growth of a function log2 |Xn|?
Scheinerman E.R., Zito J. (1994)
Constant classes: log2 |Xn| = Θ(1).
8 / 28
Boundary properties of factorial classes of graphs
Introduction
Let c(X) = 1
Question
What are possible rates of growth of a function log2 |Xn|?
Scheinerman E.R., Zito J. (1994)
Constant classes: log2 |Xn| = Θ(1).
Polynomial classes: log2 |Xn| = Θ(log n).
8 / 28
Boundary properties of factorial classes of graphs
Introduction
Let c(X) = 1
Question
What are possible rates of growth of a function log2 |Xn|?
Scheinerman E.R., Zito J. (1994)
Constant classes: log2 |Xn| = Θ(1).
Polynomial classes: log2 |Xn| = Θ(log n).
Exponential classes: log2 |Xn| = Θ(n).
8 / 28
Boundary properties of factorial classes of graphs
Introduction
Let c(X) = 1
Question
What are possible rates of growth of a function log2 |Xn|?
Scheinerman E.R., Zito J. (1994)
Constant classes: log2 |Xn| = Θ(1).
Polynomial classes: log2 |Xn| = Θ(log n).
Exponential classes: log2 |Xn| = Θ(n).
Factorial classes: log2 |Xn| = Θ(n log n).
8 / 28
Boundary properties of factorial classes of graphs
Introduction
Let c(X) = 1
Question
What are possible rates of growth of a function log2 |Xn|?
Scheinerman E.R., Zito J. (1994)
Constant classes: log2 |Xn| = Θ(1).
Polynomial classes: log2 |Xn| = Θ(log n).
Exponential classes: log2 |Xn| = Θ(n).
Factorial classes: log2 |Xn| = Θ(n log n).
All other classes are superfactorial.
8 / 28
Boundary properties of factorial classes of graphs
Introduction
Let c(X) = 1
Question
What are possible rates of growth of a function log2 |Xn|?
Scheinerman E.R., Zito J. (1994)
Constant classes: log2 |Xn| = Θ(1).
Polynomial classes: log2 |Xn| = Θ(log n).
Exponential classes: log2 |Xn| = Θ(n).
Factorial classes: log2 |Xn| = Θ(n log n).
All other classes are superfactorial.
There are no intermediate growth rates between first four ranges.
For exmaple, there is no hereditary class X with
log2 |Xn| = Θ(
√
n).
8 / 28
Boundary properties of factorial classes of graphs
Introduction
Constant
Polynomial
Exponential
Factorial layer
Classes with index 1
9 / 28
Boundary properties of factorial classes of graphs
Introduction
Example
Constant class: Co – complete graphs (1).
10 / 28
Boundary properties of factorial classes of graphs
Introduction
Example
Constant class: Co – complete graphs (1).
Polynomial class: E1 – graphs with at most one edge
( n
2 + 1).
10 / 28
Boundary properties of factorial classes of graphs
Introduction
Example
Constant class: Co – complete graphs (1).
Polynomial class: E1 – graphs with at most one edge
( n
2 + 1).
Exponential class: Co + Co (2n−1).
10 / 28
Boundary properties of factorial classes of graphs
Introduction
Example
Constant class: Co – complete graphs (1).
Polynomial class: E1 – graphs with at most one edge
( n
2 + 1).
Exponential class: Co + Co (2n−1).
Factorial class: F – forests (nn−2 < |Fn| < n2n).
10 / 28
Boundary properties of factorial classes of graphs
Introduction
Alekseev V.E. (1997)
Constant classes: log2 |Xn| = Θ(1).
Polynomial classes: log2 |Xn| = Θ(log n).
Exponential classes: log2 |Xn| = Θ(n).
Factorial classes: log2 |Xn| = Θ(n log n).
All other classes are superfactorial.
11 / 28
Boundary properties of factorial classes of graphs
Introduction
Alekseev V.E. (1997)
Constant classes: log2 |Xn| = Θ(1).
Polynomial classes: log2 |Xn| = Θ(log n).
Exponential classes: log2 |Xn| = Θ(n).
Factorial classes: log2 |Xn| = Θ(n log n).
All other classes are superfactorial.
1 Structural characterizations were obtained for the first three
layers.
2 In every of the four layers all minimal classes were found.
11 / 28
Boundary properties of factorial classes of graphs
Introduction
Constant
Polynomial
Exponential
Factorial layer
Classes with index 1
12 / 28
Boundary properties of factorial classes of graphs
Introduction
Balogh J., Bollob´as B., Weinreich D. (2000)
Constant classes: log2 |Xn| = Θ(1).
Polynomial classes: log2 |Xn| = Θ(log n).
Exponential classes: log2 |Xn| = Θ(n).
Factorial classes: log2 |Xn| = Θ(n log n).
All other classes are superfactorial.
13 / 28
Boundary properties of factorial classes of graphs
Introduction
Balogh J., Bollob´as B., Weinreich D. (2000)
Constant classes: log2 |Xn| = Θ(1).
Polynomial classes: log2 |Xn| = Θ(log n).
Exponential classes: log2 |Xn| = Θ(n).
Factorial classes: log2 |Xn| = Θ(n log n).
All other classes are superfactorial.
In addition
1 Characterized lower part of the factorial layer, i.e. classes with
|Xn| < n(1+o(1))n.
13 / 28
Boundary properties of factorial classes of graphs
Introduction
Examples of factorial classes:
forests
planar graphs
line graphs
cographs
permutation graphs
threshold graphs
graphs of bounded vertex degree
graphs of bounded clique-width
et al.
14 / 28
Boundary properties of factorial classes of graphs
Introduction
Problem
Characterize factorial layer.
15 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Minimal superfactorial classes
16 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Minimal superfactorial classes
Constant
Polynomial
Exponential
Factorial
Classes with index 1
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Minimal superfactorial classes
Constant
Polynomial
Exponential
Factorial
Classes with index 1
? ? ?
17 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Minimal superfactorial classes
log2 |Xn| = Θ(n log2
n)
18 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Minimal superfactorial classes
log2 |Xn| = Θ(n log2
n)
CB = Free(C3, C5, C6, C7, . . .)
18 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Minimal superfactorial classes
log2 |Xn| = Θ(n log2
n)
CB = Free(C3, C5, C6, C7, . . .)
Theorem (Spinrad J. P., 1995)
log2 |CBn| = Θ(n log2
n)
18 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Minimal superfactorial classes
log2 |Xn| = Θ(n log2
n)
CB = Free(C3, C5, C6, C7, . . .)
Theorem (Spinrad J. P., 1995)
log2 |CBn| = Θ(n log2
n)
Question
Is the class of chordal bipartite graphs a minimal superfactorial?
18 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Minimal superfactorial classes
Theorem (Dabrowski K., Lozin V.V., Zamaraev V., 2012)
Let X = Free(2C4, 2C4 + e) ∩ CB. Then log2 |Xn| = Θ(n log2
n).
2C4 2C4 + e
19 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Minimal superfactorial classes
Theorem (Dabrowski K., Lozin V.V., Zamaraev V., 2012)
Let X = Free(2C4, 2C4 + e) ∩ CB. Then log2 |Xn| = Θ(n log2
n).
2C4 2C4 + e
Open question
Is the class Free(2C4, 2C4 + e) ∩ CB a minimal superfactorial?
19 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Minimal superfactorial classes
Denote by Bk the class of (C4, C6, ..., C2k)-free bipartite graphs.
20 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Minimal superfactorial classes
Denote by Bk the class of (C4, C6, ..., C2k)-free bipartite graphs.
Statement (follows from the results of Lazebnik F., et al., 1995)
For each integer k ≥ 2, the class Bk is superfactorial.
20 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Minimal superfactorial classes
Denote by Bk the class of (C4, C6, ..., C2k)-free bipartite graphs.
Statement (follows from the results of Lazebnik F., et al., 1995)
For each integer k ≥ 2, the class Bk is superfactorial.
Infinite sequence of superfactorial classes
B2 ⊃ B3 ⊃ B4 . . . .
20 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Minimal superfactorial classes
Denote by Bk the class of (C4, C6, ..., C2k)-free bipartite graphs.
Statement (follows from the results of Lazebnik F., et al., 1995)
For each integer k ≥ 2, the class Bk is superfactorial.
Infinite sequence of superfactorial classes
B2 ⊃ B3 ⊃ B4 . . . .
In this sequence there is no minimal superfactorial class.
20 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Limit classes
Definition
Given a sequence X1 ⊇ X2 ⊇ X3 ⊇ . . . of graph classes, we will
say that the sequence converges to a class X if
i≥1
Xi = X.
21 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Limit classes
Definition
Given a sequence X1 ⊇ X2 ⊇ X3 ⊇ . . . of graph classes, we will
say that the sequence converges to a class X if
i≥1
Xi = X.
Example
The sequence B2 ⊃ B3 ⊃ B4 . . . converges to the factorial class F
of forests, i.e.
i≥1
Bi = F.
21 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Limit classes
Definition
Given a sequence X1 ⊇ X2 ⊇ X3 ⊇ . . . of graph classes, we will
say that the sequence converges to a class X if
i≥1
Xi = X.
Example
The sequence B2 ⊃ B3 ⊃ B4 . . . converges to the factorial class F
of forests, i.e.
i≥1
Bi = F.
Definition
A class X of graphs is a limit class (for the factorial layer) if there
is a sequence of superfactorial classes converging to X.
21 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Boundary classes
Definition
A limit class is called boundary (or minimal) if it does not properly
contain any other limit class.
22 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Boundary classes
Definition
A limit class is called boundary (or minimal) if it does not properly
contain any other limit class.
Theorem
A finitely defined class is superfactorial if and only if it contains a
boundary class.
22 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Boundary classes
Definition
A limit class is called boundary (or minimal) if it does not properly
contain any other limit class.
Theorem
A finitely defined class is superfactorial if and only if it contains a
boundary class.
Theorem
The class of forests is a boundary class.
22 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Are there more boundary classes?
There are five more boundary classes, which can be easly obtained
from the class of forests.
23 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Are there more boundary classes?
There are five more boundary classes, which can be easly obtained
from the class of forests.
Two of them are:
1 complements of forests;
2 bipartite complements of forests;
23 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Are there more boundary classes?
There are five more boundary classes, which can be easly obtained
from the class of forests.
Two of them are:
1 complements of forests;
2 bipartite complements of forests;
1
5
2
6
3
7
4
8
F
1
5
2
6
3
7
4
8
Bipartite complement of F
23 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Are there more boundary classes?
There are five more boundary classes, which can be easly obtained
from the class of forests.
Two of them are:
1 complements of forests;
2 bipartite complements of forests;
1
5
2
6
3
7
4
8
F
1
5
2
6
3
7
4
8
Bipartite complement of F
Question
Are there other boundary classes?
23 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Lozin’s conjecture
Conjecture (Lozin’s conjecture, [Lozin V.V., Mayhill C., Zamaraev V., 2011])
A hereditary graph class X is factorial if and only if at least one of
the following three classes: X ∩ B, X ∩ B и X ∩ S is factorial and
each of these classes is at most factorial.
B – bipartite graphs
B – complements of bipartite graphs
S – split graphs
24 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Proper boundary subclasses
B2 = Free(C4) ∩ B CB = Free(C3, C5, C6, . . .)
25 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Proper boundary subclasses
B2 = Free(C4) ∩ B CB = Free(C3, C5, C6, . . .)
superfactorial superfactorial
25 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Proper boundary subclasses
B2 = Free(C4) ∩ B CB = Free(C3, C5, C6, . . .)
superfactorial superfactorial
i≥1
Bi = F ⊂ B2
i≥1
Bi = F ⊂ CB
25 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Proper boundary subclasses
B2 = Free(C4) ∩ B CB = Free(C3, C5, C6, . . .)
superfactorial superfactorial
i≥1
Bi = F ⊂ B2
i≥1
Bi = F ⊂ CB
Bi ⊆ B2, i ≥ 1 Bi CB, i ≥ 1
25 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Proper boundary subclasses
B2 = Free(C4) ∩ B CB = Free(C3, C5, C6, . . .)
superfactorial superfactorial
i≥1
Bi = F ⊂ B2
i≥1
Bi = F ⊂ CB
Bi ⊆ B2, i ≥ 1 Bi CB, i ≥ 1
Definition
Let X be a superfactorial class and S a boundary subclass
contained in X. We say that S is a proper boundary subclass of X
if there is a sequence of superfactorial subclasses of X converging
to S.
25 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Proper boundary subclasses
Theorem
There are no proper boundary subclasses of chordal bipartite
graphs.
26 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Proper boundary subclasses
Theorem
There are no proper boundary subclasses of chordal bipartite
graphs.
Theorem
The class of forests is the only proper boundary subclass of B2.
26 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Open problems
Open question
Find a minimal superfactorial class.
27 / 28
Boundary properties of factorial classes of graphs
Minimal superfactorial classes
Open problems
Open question
Find a minimal superfactorial class.
Open question
Is the list of boundary classes we found complete?
27 / 28
Thank you!

Mais conteúdo relacionado

Mais procurados

A discussion on sampling graphs to approximate network classification functions
A discussion on sampling graphs to approximate network classification functionsA discussion on sampling graphs to approximate network classification functions
A discussion on sampling graphs to approximate network classification functionsLARCA UPC
 
CBSE Class 12 Mathematics formulas
CBSE Class 12 Mathematics formulasCBSE Class 12 Mathematics formulas
CBSE Class 12 Mathematics formulasParth Kshirsagar
 
Lecture 11 diagonalization & complex eigenvalues - 5-3 & 5-5
Lecture  11   diagonalization & complex eigenvalues -  5-3 & 5-5Lecture  11   diagonalization & complex eigenvalues -  5-3 & 5-5
Lecture 11 diagonalization & complex eigenvalues - 5-3 & 5-5njit-ronbrown
 
Linear vs. quadratic classifier power point
Linear vs. quadratic classifier power pointLinear vs. quadratic classifier power point
Linear vs. quadratic classifier power pointAlaa Tharwat
 
Specific function examples
Specific function examplesSpecific function examples
Specific function examplesLeo Crisologo
 
Lecture 9 eigenvalues - 5-1 & 5-2
Lecture 9   eigenvalues -  5-1 & 5-2Lecture 9   eigenvalues -  5-1 & 5-2
Lecture 9 eigenvalues - 5-1 & 5-2njit-ronbrown
 
Advanced algebra (some terminologies)
Advanced algebra (some terminologies)Advanced algebra (some terminologies)
Advanced algebra (some terminologies)aufpaulalonzo
 
4. Linear Algebra for Machine Learning: Eigenvalues, Eigenvectors and Diagona...
4. Linear Algebra for Machine Learning: Eigenvalues, Eigenvectors and Diagona...4. Linear Algebra for Machine Learning: Eigenvalues, Eigenvectors and Diagona...
4. Linear Algebra for Machine Learning: Eigenvalues, Eigenvectors and Diagona...Ceni Babaoglu, PhD
 
013_20160328_Topological_Measurement_Of_Protein_Compressibility
013_20160328_Topological_Measurement_Of_Protein_Compressibility013_20160328_Topological_Measurement_Of_Protein_Compressibility
013_20160328_Topological_Measurement_Of_Protein_CompressibilityHa Phuong
 
Lecture 7 determinants cramers spaces - section 3-2 3-3 and 4-1
Lecture 7   determinants cramers spaces - section 3-2 3-3 and 4-1Lecture 7   determinants cramers spaces - section 3-2 3-3 and 4-1
Lecture 7 determinants cramers spaces - section 3-2 3-3 and 4-1njit-ronbrown
 
Density theorems for anisotropic point configurations
Density theorems for anisotropic point configurationsDensity theorems for anisotropic point configurations
Density theorems for anisotropic point configurationsVjekoslavKovac1
 
8th alg -l4.1--nov26
8th alg -l4.1--nov268th alg -l4.1--nov26
8th alg -l4.1--nov26jdurst65
 
 Igcse mathematics additional standards
 Igcse   mathematics additional standards Igcse   mathematics additional standards
 Igcse mathematics additional standardsRoss
 
Database systems-Formal relational query languages
Database systems-Formal relational query languagesDatabase systems-Formal relational query languages
Database systems-Formal relational query languagesjamunaashok
 
Sat math overview from college board
Sat math overview from college boardSat math overview from college board
Sat math overview from college boardYoAmoNYC
 
5. Linear Algebra for Machine Learning: Singular Value Decomposition and Prin...
5. Linear Algebra for Machine Learning: Singular Value Decomposition and Prin...5. Linear Algebra for Machine Learning: Singular Value Decomposition and Prin...
5. Linear Algebra for Machine Learning: Singular Value Decomposition and Prin...Ceni Babaoglu, PhD
 

Mais procurados (20)

A discussion on sampling graphs to approximate network classification functions
A discussion on sampling graphs to approximate network classification functionsA discussion on sampling graphs to approximate network classification functions
A discussion on sampling graphs to approximate network classification functions
 
Relations and functions
Relations and functionsRelations and functions
Relations and functions
 
CBSE Class 12 Mathematics formulas
CBSE Class 12 Mathematics formulasCBSE Class 12 Mathematics formulas
CBSE Class 12 Mathematics formulas
 
Lecture 11 diagonalization & complex eigenvalues - 5-3 & 5-5
Lecture  11   diagonalization & complex eigenvalues -  5-3 & 5-5Lecture  11   diagonalization & complex eigenvalues -  5-3 & 5-5
Lecture 11 diagonalization & complex eigenvalues - 5-3 & 5-5
 
Linear vs. quadratic classifier power point
Linear vs. quadratic classifier power pointLinear vs. quadratic classifier power point
Linear vs. quadratic classifier power point
 
Specific function examples
Specific function examplesSpecific function examples
Specific function examples
 
Lecture 9 eigenvalues - 5-1 & 5-2
Lecture 9   eigenvalues -  5-1 & 5-2Lecture 9   eigenvalues -  5-1 & 5-2
Lecture 9 eigenvalues - 5-1 & 5-2
 
Advanced algebra (some terminologies)
Advanced algebra (some terminologies)Advanced algebra (some terminologies)
Advanced algebra (some terminologies)
 
4. Linear Algebra for Machine Learning: Eigenvalues, Eigenvectors and Diagona...
4. Linear Algebra for Machine Learning: Eigenvalues, Eigenvectors and Diagona...4. Linear Algebra for Machine Learning: Eigenvalues, Eigenvectors and Diagona...
4. Linear Algebra for Machine Learning: Eigenvalues, Eigenvectors and Diagona...
 
013_20160328_Topological_Measurement_Of_Protein_Compressibility
013_20160328_Topological_Measurement_Of_Protein_Compressibility013_20160328_Topological_Measurement_Of_Protein_Compressibility
013_20160328_Topological_Measurement_Of_Protein_Compressibility
 
Lecture 7 determinants cramers spaces - section 3-2 3-3 and 4-1
Lecture 7   determinants cramers spaces - section 3-2 3-3 and 4-1Lecture 7   determinants cramers spaces - section 3-2 3-3 and 4-1
Lecture 7 determinants cramers spaces - section 3-2 3-3 and 4-1
 
Density theorems for anisotropic point configurations
Density theorems for anisotropic point configurationsDensity theorems for anisotropic point configurations
Density theorems for anisotropic point configurations
 
Modeling the dynamics of molecular concentration during the diffusion procedure
Modeling the dynamics of molecular concentration during the  diffusion procedureModeling the dynamics of molecular concentration during the  diffusion procedure
Modeling the dynamics of molecular concentration during the diffusion procedure
 
Lecture2 xing
Lecture2 xingLecture2 xing
Lecture2 xing
 
8th alg -l4.1--nov26
8th alg -l4.1--nov268th alg -l4.1--nov26
8th alg -l4.1--nov26
 
Analytic function
Analytic functionAnalytic function
Analytic function
 
 Igcse mathematics additional standards
 Igcse   mathematics additional standards Igcse   mathematics additional standards
 Igcse mathematics additional standards
 
Database systems-Formal relational query languages
Database systems-Formal relational query languagesDatabase systems-Formal relational query languages
Database systems-Formal relational query languages
 
Sat math overview from college board
Sat math overview from college boardSat math overview from college board
Sat math overview from college board
 
5. Linear Algebra for Machine Learning: Singular Value Decomposition and Prin...
5. Linear Algebra for Machine Learning: Singular Value Decomposition and Prin...5. Linear Algebra for Machine Learning: Singular Value Decomposition and Prin...
5. Linear Algebra for Machine Learning: Singular Value Decomposition and Prin...
 

Semelhante a Victor Zamaraev – Boundary properties of factorial classes of graphs

Density theorems for Euclidean point configurations
Density theorems for Euclidean point configurationsDensity theorems for Euclidean point configurations
Density theorems for Euclidean point configurationsVjekoslavKovac1
 
Classification and regression based on derivatives: a consistency result for ...
Classification and regression based on derivatives: a consistency result for ...Classification and regression based on derivatives: a consistency result for ...
Classification and regression based on derivatives: a consistency result for ...tuxette
 
Density theorems for anisotropic point configurations
Density theorems for anisotropic point configurationsDensity theorems for anisotropic point configurations
Density theorems for anisotropic point configurationsVjekoslavKovac1
 
Seismic data processing lecture 3
Seismic data processing lecture 3Seismic data processing lecture 3
Seismic data processing lecture 3Amin khalil
 
Conditional Random Fields
Conditional Random FieldsConditional Random Fields
Conditional Random Fieldslswing
 
Convolution and FFT
Convolution and FFTConvolution and FFT
Convolution and FFTChenghao Jin
 
An Introduction to Spectral Graph Theory
An Introduction to Spectral Graph TheoryAn Introduction to Spectral Graph Theory
An Introduction to Spectral Graph Theoryjoisino
 
A new implementation of k-MLE for mixture modelling of Wishart distributions
A new implementation of k-MLE for mixture modelling of Wishart distributionsA new implementation of k-MLE for mixture modelling of Wishart distributions
A new implementation of k-MLE for mixture modelling of Wishart distributionsFrank Nielsen
 
On learning statistical mixtures maximizing the complete likelihood
On learning statistical mixtures maximizing the complete likelihoodOn learning statistical mixtures maximizing the complete likelihood
On learning statistical mixtures maximizing the complete likelihoodFrank Nielsen
 
Thesis oral defense
Thesis oral defenseThesis oral defense
Thesis oral defenseFan Zhitao
 
Many electrons atoms_2012.12.04 (PDF with links
Many electrons atoms_2012.12.04 (PDF with linksMany electrons atoms_2012.12.04 (PDF with links
Many electrons atoms_2012.12.04 (PDF with linksLadislav Kocbach
 
Maths 12 supporting material by cbse
Maths 12 supporting material by cbseMaths 12 supporting material by cbse
Maths 12 supporting material by cbsenitishguptamaps
 
A T(1)-type theorem for entangled multilinear Calderon-Zygmund operators
A T(1)-type theorem for entangled multilinear Calderon-Zygmund operatorsA T(1)-type theorem for entangled multilinear Calderon-Zygmund operators
A T(1)-type theorem for entangled multilinear Calderon-Zygmund operatorsVjekoslavKovac1
 
Dialectica and Kolmogorov Problems
Dialectica and Kolmogorov ProblemsDialectica and Kolmogorov Problems
Dialectica and Kolmogorov ProblemsValeria de Paiva
 

Semelhante a Victor Zamaraev – Boundary properties of factorial classes of graphs (20)

1 - Linear Regression
1 - Linear Regression1 - Linear Regression
1 - Linear Regression
 
ma112011id535
ma112011id535ma112011id535
ma112011id535
 
Density theorems for Euclidean point configurations
Density theorems for Euclidean point configurationsDensity theorems for Euclidean point configurations
Density theorems for Euclidean point configurations
 
Classification and regression based on derivatives: a consistency result for ...
Classification and regression based on derivatives: a consistency result for ...Classification and regression based on derivatives: a consistency result for ...
Classification and regression based on derivatives: a consistency result for ...
 
tutorial6
tutorial6tutorial6
tutorial6
 
Density theorems for anisotropic point configurations
Density theorems for anisotropic point configurationsDensity theorems for anisotropic point configurations
Density theorems for anisotropic point configurations
 
g-lecture.pptx
g-lecture.pptxg-lecture.pptx
g-lecture.pptx
 
Seismic data processing lecture 3
Seismic data processing lecture 3Seismic data processing lecture 3
Seismic data processing lecture 3
 
Conditional Random Fields
Conditional Random FieldsConditional Random Fields
Conditional Random Fields
 
Convolution and FFT
Convolution and FFTConvolution and FFT
Convolution and FFT
 
An Introduction to Spectral Graph Theory
An Introduction to Spectral Graph TheoryAn Introduction to Spectral Graph Theory
An Introduction to Spectral Graph Theory
 
A new implementation of k-MLE for mixture modelling of Wishart distributions
A new implementation of k-MLE for mixture modelling of Wishart distributionsA new implementation of k-MLE for mixture modelling of Wishart distributions
A new implementation of k-MLE for mixture modelling of Wishart distributions
 
On learning statistical mixtures maximizing the complete likelihood
On learning statistical mixtures maximizing the complete likelihoodOn learning statistical mixtures maximizing the complete likelihood
On learning statistical mixtures maximizing the complete likelihood
 
Lecture_note2.pdf
Lecture_note2.pdfLecture_note2.pdf
Lecture_note2.pdf
 
Thesis oral defense
Thesis oral defenseThesis oral defense
Thesis oral defense
 
Many electrons atoms_2012.12.04 (PDF with links
Many electrons atoms_2012.12.04 (PDF with linksMany electrons atoms_2012.12.04 (PDF with links
Many electrons atoms_2012.12.04 (PDF with links
 
Maths 12 supporting material by cbse
Maths 12 supporting material by cbseMaths 12 supporting material by cbse
Maths 12 supporting material by cbse
 
A T(1)-type theorem for entangled multilinear Calderon-Zygmund operators
A T(1)-type theorem for entangled multilinear Calderon-Zygmund operatorsA T(1)-type theorem for entangled multilinear Calderon-Zygmund operators
A T(1)-type theorem for entangled multilinear Calderon-Zygmund operators
 
Irjet v2i170
Irjet v2i170Irjet v2i170
Irjet v2i170
 
Dialectica and Kolmogorov Problems
Dialectica and Kolmogorov ProblemsDialectica and Kolmogorov Problems
Dialectica and Kolmogorov Problems
 

Mais de Yandex

Предсказание оттока игроков из World of Tanks
Предсказание оттока игроков из World of TanksПредсказание оттока игроков из World of Tanks
Предсказание оттока игроков из World of TanksYandex
 
Как принять/организовать работу по поисковой оптимизации сайта, Сергей Царик,...
Как принять/организовать работу по поисковой оптимизации сайта, Сергей Царик,...Как принять/организовать работу по поисковой оптимизации сайта, Сергей Царик,...
Как принять/организовать работу по поисковой оптимизации сайта, Сергей Царик,...Yandex
 
Структурированные данные, Юлия Тихоход, лекция в Школе вебмастеров Яндекса
Структурированные данные, Юлия Тихоход, лекция в Школе вебмастеров ЯндексаСтруктурированные данные, Юлия Тихоход, лекция в Школе вебмастеров Яндекса
Структурированные данные, Юлия Тихоход, лекция в Школе вебмастеров ЯндексаYandex
 
Представление сайта в поиске, Сергей Лысенко, лекция в Школе вебмастеров Яндекса
Представление сайта в поиске, Сергей Лысенко, лекция в Школе вебмастеров ЯндексаПредставление сайта в поиске, Сергей Лысенко, лекция в Школе вебмастеров Яндекса
Представление сайта в поиске, Сергей Лысенко, лекция в Школе вебмастеров ЯндексаYandex
 
Плохие методы продвижения сайта, Екатерины Гладких, лекция в Школе вебмастеро...
Плохие методы продвижения сайта, Екатерины Гладких, лекция в Школе вебмастеро...Плохие методы продвижения сайта, Екатерины Гладких, лекция в Школе вебмастеро...
Плохие методы продвижения сайта, Екатерины Гладких, лекция в Школе вебмастеро...Yandex
 
Основные принципы ранжирования, Сергей Царик и Антон Роменский, лекция в Школ...
Основные принципы ранжирования, Сергей Царик и Антон Роменский, лекция в Школ...Основные принципы ранжирования, Сергей Царик и Антон Роменский, лекция в Школ...
Основные принципы ранжирования, Сергей Царик и Антон Роменский, лекция в Школ...Yandex
 
Основные принципы индексирования сайта, Александр Смирнов, лекция в Школе веб...
Основные принципы индексирования сайта, Александр Смирнов, лекция в Школе веб...Основные принципы индексирования сайта, Александр Смирнов, лекция в Школе веб...
Основные принципы индексирования сайта, Александр Смирнов, лекция в Школе веб...Yandex
 
Мобильное приложение: как и зачем, Александр Лукин, лекция в Школе вебмастеро...
Мобильное приложение: как и зачем, Александр Лукин, лекция в Школе вебмастеро...Мобильное приложение: как и зачем, Александр Лукин, лекция в Школе вебмастеро...
Мобильное приложение: как и зачем, Александр Лукин, лекция в Школе вебмастеро...Yandex
 
Сайты на мобильных устройствах, Олег Ножичкин, лекция в Школе вебмастеров Янд...
Сайты на мобильных устройствах, Олег Ножичкин, лекция в Школе вебмастеров Янд...Сайты на мобильных устройствах, Олег Ножичкин, лекция в Школе вебмастеров Янд...
Сайты на мобильных устройствах, Олег Ножичкин, лекция в Школе вебмастеров Янд...Yandex
 
Качественная аналитика сайта, Юрий Батиевский, лекция в Школе вебмастеров Янд...
Качественная аналитика сайта, Юрий Батиевский, лекция в Школе вебмастеров Янд...Качественная аналитика сайта, Юрий Батиевский, лекция в Школе вебмастеров Янд...
Качественная аналитика сайта, Юрий Батиевский, лекция в Школе вебмастеров Янд...Yandex
 
Что можно и что нужно измерять на сайте, Петр Аброськин, лекция в Школе вебма...
Что можно и что нужно измерять на сайте, Петр Аброськин, лекция в Школе вебма...Что можно и что нужно измерять на сайте, Петр Аброськин, лекция в Школе вебма...
Что можно и что нужно измерять на сайте, Петр Аброськин, лекция в Школе вебма...Yandex
 
Как правильно поставить ТЗ на создание сайта, Алексей Бородкин, лекция в Школ...
Как правильно поставить ТЗ на создание сайта, Алексей Бородкин, лекция в Школ...Как правильно поставить ТЗ на создание сайта, Алексей Бородкин, лекция в Школ...
Как правильно поставить ТЗ на создание сайта, Алексей Бородкин, лекция в Школ...Yandex
 
Как защитить свой сайт, Пётр Волков, лекция в Школе вебмастеров
Как защитить свой сайт, Пётр Волков, лекция в Школе вебмастеровКак защитить свой сайт, Пётр Волков, лекция в Школе вебмастеров
Как защитить свой сайт, Пётр Волков, лекция в Школе вебмастеровYandex
 
Как правильно составить структуру сайта, Дмитрий Сатин, лекция в Школе вебмас...
Как правильно составить структуру сайта, Дмитрий Сатин, лекция в Школе вебмас...Как правильно составить структуру сайта, Дмитрий Сатин, лекция в Школе вебмас...
Как правильно составить структуру сайта, Дмитрий Сатин, лекция в Школе вебмас...Yandex
 
Технические особенности создания сайта, Дмитрий Васильева, лекция в Школе веб...
Технические особенности создания сайта, Дмитрий Васильева, лекция в Школе веб...Технические особенности создания сайта, Дмитрий Васильева, лекция в Школе веб...
Технические особенности создания сайта, Дмитрий Васильева, лекция в Школе веб...Yandex
 
Конструкторы для отдельных элементов сайта, Елена Першина, лекция в Школе веб...
Конструкторы для отдельных элементов сайта, Елена Першина, лекция в Школе веб...Конструкторы для отдельных элементов сайта, Елена Першина, лекция в Школе веб...
Конструкторы для отдельных элементов сайта, Елена Першина, лекция в Школе веб...Yandex
 
Контент для интернет-магазинов, Катерина Ерошина, лекция в Школе вебмастеров ...
Контент для интернет-магазинов, Катерина Ерошина, лекция в Школе вебмастеров ...Контент для интернет-магазинов, Катерина Ерошина, лекция в Школе вебмастеров ...
Контент для интернет-магазинов, Катерина Ерошина, лекция в Школе вебмастеров ...Yandex
 
Как написать хороший текст для сайта, Катерина Ерошина, лекция в Школе вебмас...
Как написать хороший текст для сайта, Катерина Ерошина, лекция в Школе вебмас...Как написать хороший текст для сайта, Катерина Ерошина, лекция в Школе вебмас...
Как написать хороший текст для сайта, Катерина Ерошина, лекция в Школе вебмас...Yandex
 
Usability и дизайн - как не помешать пользователю, Алексей Иванов, лекция в Ш...
Usability и дизайн - как не помешать пользователю, Алексей Иванов, лекция в Ш...Usability и дизайн - как не помешать пользователю, Алексей Иванов, лекция в Ш...
Usability и дизайн - как не помешать пользователю, Алексей Иванов, лекция в Ш...Yandex
 
Cайт. Зачем он и каким должен быть, Алексей Иванов, лекция в Школе вебмастеро...
Cайт. Зачем он и каким должен быть, Алексей Иванов, лекция в Школе вебмастеро...Cайт. Зачем он и каким должен быть, Алексей Иванов, лекция в Школе вебмастеро...
Cайт. Зачем он и каким должен быть, Алексей Иванов, лекция в Школе вебмастеро...Yandex
 

Mais de Yandex (20)

Предсказание оттока игроков из World of Tanks
Предсказание оттока игроков из World of TanksПредсказание оттока игроков из World of Tanks
Предсказание оттока игроков из World of Tanks
 
Как принять/организовать работу по поисковой оптимизации сайта, Сергей Царик,...
Как принять/организовать работу по поисковой оптимизации сайта, Сергей Царик,...Как принять/организовать работу по поисковой оптимизации сайта, Сергей Царик,...
Как принять/организовать работу по поисковой оптимизации сайта, Сергей Царик,...
 
Структурированные данные, Юлия Тихоход, лекция в Школе вебмастеров Яндекса
Структурированные данные, Юлия Тихоход, лекция в Школе вебмастеров ЯндексаСтруктурированные данные, Юлия Тихоход, лекция в Школе вебмастеров Яндекса
Структурированные данные, Юлия Тихоход, лекция в Школе вебмастеров Яндекса
 
Представление сайта в поиске, Сергей Лысенко, лекция в Школе вебмастеров Яндекса
Представление сайта в поиске, Сергей Лысенко, лекция в Школе вебмастеров ЯндексаПредставление сайта в поиске, Сергей Лысенко, лекция в Школе вебмастеров Яндекса
Представление сайта в поиске, Сергей Лысенко, лекция в Школе вебмастеров Яндекса
 
Плохие методы продвижения сайта, Екатерины Гладких, лекция в Школе вебмастеро...
Плохие методы продвижения сайта, Екатерины Гладких, лекция в Школе вебмастеро...Плохие методы продвижения сайта, Екатерины Гладких, лекция в Школе вебмастеро...
Плохие методы продвижения сайта, Екатерины Гладких, лекция в Школе вебмастеро...
 
Основные принципы ранжирования, Сергей Царик и Антон Роменский, лекция в Школ...
Основные принципы ранжирования, Сергей Царик и Антон Роменский, лекция в Школ...Основные принципы ранжирования, Сергей Царик и Антон Роменский, лекция в Школ...
Основные принципы ранжирования, Сергей Царик и Антон Роменский, лекция в Школ...
 
Основные принципы индексирования сайта, Александр Смирнов, лекция в Школе веб...
Основные принципы индексирования сайта, Александр Смирнов, лекция в Школе веб...Основные принципы индексирования сайта, Александр Смирнов, лекция в Школе веб...
Основные принципы индексирования сайта, Александр Смирнов, лекция в Школе веб...
 
Мобильное приложение: как и зачем, Александр Лукин, лекция в Школе вебмастеро...
Мобильное приложение: как и зачем, Александр Лукин, лекция в Школе вебмастеро...Мобильное приложение: как и зачем, Александр Лукин, лекция в Школе вебмастеро...
Мобильное приложение: как и зачем, Александр Лукин, лекция в Школе вебмастеро...
 
Сайты на мобильных устройствах, Олег Ножичкин, лекция в Школе вебмастеров Янд...
Сайты на мобильных устройствах, Олег Ножичкин, лекция в Школе вебмастеров Янд...Сайты на мобильных устройствах, Олег Ножичкин, лекция в Школе вебмастеров Янд...
Сайты на мобильных устройствах, Олег Ножичкин, лекция в Школе вебмастеров Янд...
 
Качественная аналитика сайта, Юрий Батиевский, лекция в Школе вебмастеров Янд...
Качественная аналитика сайта, Юрий Батиевский, лекция в Школе вебмастеров Янд...Качественная аналитика сайта, Юрий Батиевский, лекция в Школе вебмастеров Янд...
Качественная аналитика сайта, Юрий Батиевский, лекция в Школе вебмастеров Янд...
 
Что можно и что нужно измерять на сайте, Петр Аброськин, лекция в Школе вебма...
Что можно и что нужно измерять на сайте, Петр Аброськин, лекция в Школе вебма...Что можно и что нужно измерять на сайте, Петр Аброськин, лекция в Школе вебма...
Что можно и что нужно измерять на сайте, Петр Аброськин, лекция в Школе вебма...
 
Как правильно поставить ТЗ на создание сайта, Алексей Бородкин, лекция в Школ...
Как правильно поставить ТЗ на создание сайта, Алексей Бородкин, лекция в Школ...Как правильно поставить ТЗ на создание сайта, Алексей Бородкин, лекция в Школ...
Как правильно поставить ТЗ на создание сайта, Алексей Бородкин, лекция в Школ...
 
Как защитить свой сайт, Пётр Волков, лекция в Школе вебмастеров
Как защитить свой сайт, Пётр Волков, лекция в Школе вебмастеровКак защитить свой сайт, Пётр Волков, лекция в Школе вебмастеров
Как защитить свой сайт, Пётр Волков, лекция в Школе вебмастеров
 
Как правильно составить структуру сайта, Дмитрий Сатин, лекция в Школе вебмас...
Как правильно составить структуру сайта, Дмитрий Сатин, лекция в Школе вебмас...Как правильно составить структуру сайта, Дмитрий Сатин, лекция в Школе вебмас...
Как правильно составить структуру сайта, Дмитрий Сатин, лекция в Школе вебмас...
 
Технические особенности создания сайта, Дмитрий Васильева, лекция в Школе веб...
Технические особенности создания сайта, Дмитрий Васильева, лекция в Школе веб...Технические особенности создания сайта, Дмитрий Васильева, лекция в Школе веб...
Технические особенности создания сайта, Дмитрий Васильева, лекция в Школе веб...
 
Конструкторы для отдельных элементов сайта, Елена Першина, лекция в Школе веб...
Конструкторы для отдельных элементов сайта, Елена Першина, лекция в Школе веб...Конструкторы для отдельных элементов сайта, Елена Першина, лекция в Школе веб...
Конструкторы для отдельных элементов сайта, Елена Першина, лекция в Школе веб...
 
Контент для интернет-магазинов, Катерина Ерошина, лекция в Школе вебмастеров ...
Контент для интернет-магазинов, Катерина Ерошина, лекция в Школе вебмастеров ...Контент для интернет-магазинов, Катерина Ерошина, лекция в Школе вебмастеров ...
Контент для интернет-магазинов, Катерина Ерошина, лекция в Школе вебмастеров ...
 
Как написать хороший текст для сайта, Катерина Ерошина, лекция в Школе вебмас...
Как написать хороший текст для сайта, Катерина Ерошина, лекция в Школе вебмас...Как написать хороший текст для сайта, Катерина Ерошина, лекция в Школе вебмас...
Как написать хороший текст для сайта, Катерина Ерошина, лекция в Школе вебмас...
 
Usability и дизайн - как не помешать пользователю, Алексей Иванов, лекция в Ш...
Usability и дизайн - как не помешать пользователю, Алексей Иванов, лекция в Ш...Usability и дизайн - как не помешать пользователю, Алексей Иванов, лекция в Ш...
Usability и дизайн - как не помешать пользователю, Алексей Иванов, лекция в Ш...
 
Cайт. Зачем он и каким должен быть, Алексей Иванов, лекция в Школе вебмастеро...
Cайт. Зачем он и каким должен быть, Алексей Иванов, лекция в Школе вебмастеро...Cайт. Зачем он и каким должен быть, Алексей Иванов, лекция в Школе вебмастеро...
Cайт. Зачем он и каким должен быть, Алексей Иванов, лекция в Школе вебмастеро...
 

Último

The Mariana Trench remarkable geological features on Earth.pptx
The Mariana Trench remarkable geological features on Earth.pptxThe Mariana Trench remarkable geological features on Earth.pptx
The Mariana Trench remarkable geological features on Earth.pptxseri bangash
 
Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...
Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...
Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...Silpa
 
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.Nitya salvi
 
Call Girls Ahmedabad +917728919243 call me Independent Escort Service
Call Girls Ahmedabad +917728919243 call me Independent Escort ServiceCall Girls Ahmedabad +917728919243 call me Independent Escort Service
Call Girls Ahmedabad +917728919243 call me Independent Escort Serviceshivanisharma5244
 
Connaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verified
Connaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verifiedConnaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verified
Connaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verifiedDelhi Call girls
 
Conjugation, transduction and transformation
Conjugation, transduction and transformationConjugation, transduction and transformation
Conjugation, transduction and transformationAreesha Ahmad
 
Proteomics: types, protein profiling steps etc.
Proteomics: types, protein profiling steps etc.Proteomics: types, protein profiling steps etc.
Proteomics: types, protein profiling steps etc.Silpa
 
PSYCHOSOCIAL NEEDS. in nursing II sem pptx
PSYCHOSOCIAL NEEDS. in nursing II sem pptxPSYCHOSOCIAL NEEDS. in nursing II sem pptx
PSYCHOSOCIAL NEEDS. in nursing II sem pptxSuji236384
 
GBSN - Microbiology (Unit 2)
GBSN - Microbiology (Unit 2)GBSN - Microbiology (Unit 2)
GBSN - Microbiology (Unit 2)Areesha Ahmad
 
Pests of cotton_Sucking_Pests_Dr.UPR.pdf
Pests of cotton_Sucking_Pests_Dr.UPR.pdfPests of cotton_Sucking_Pests_Dr.UPR.pdf
Pests of cotton_Sucking_Pests_Dr.UPR.pdfPirithiRaju
 
Dubai Call Girls Beauty Face Teen O525547819 Call Girls Dubai Young
Dubai Call Girls Beauty Face Teen O525547819 Call Girls Dubai YoungDubai Call Girls Beauty Face Teen O525547819 Call Girls Dubai Young
Dubai Call Girls Beauty Face Teen O525547819 Call Girls Dubai Youngkajalvid75
 
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 bAsymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 bSérgio Sacani
 
Factory Acceptance Test( FAT).pptx .
Factory Acceptance Test( FAT).pptx       .Factory Acceptance Test( FAT).pptx       .
Factory Acceptance Test( FAT).pptx .Poonam Aher Patil
 
Thyroid Physiology_Dr.E. Muralinath_ Associate Professor
Thyroid Physiology_Dr.E. Muralinath_ Associate ProfessorThyroid Physiology_Dr.E. Muralinath_ Associate Professor
Thyroid Physiology_Dr.E. Muralinath_ Associate Professormuralinath2
 
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....muralinath2
 
High Profile 🔝 8250077686 📞 Call Girls Service in GTB Nagar🍑
High Profile 🔝 8250077686 📞 Call Girls Service in GTB Nagar🍑High Profile 🔝 8250077686 📞 Call Girls Service in GTB Nagar🍑
High Profile 🔝 8250077686 📞 Call Girls Service in GTB Nagar🍑Damini Dixit
 
chemical bonding Essentials of Physical Chemistry2.pdf
chemical bonding Essentials of Physical Chemistry2.pdfchemical bonding Essentials of Physical Chemistry2.pdf
chemical bonding Essentials of Physical Chemistry2.pdfTukamushabaBismark
 
GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)Areesha Ahmad
 
GBSN - Biochemistry (Unit 1)
GBSN - Biochemistry (Unit 1)GBSN - Biochemistry (Unit 1)
GBSN - Biochemistry (Unit 1)Areesha Ahmad
 

Último (20)

The Mariana Trench remarkable geological features on Earth.pptx
The Mariana Trench remarkable geological features on Earth.pptxThe Mariana Trench remarkable geological features on Earth.pptx
The Mariana Trench remarkable geological features on Earth.pptx
 
Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...
Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...
Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...
 
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.
 
Call Girls Ahmedabad +917728919243 call me Independent Escort Service
Call Girls Ahmedabad +917728919243 call me Independent Escort ServiceCall Girls Ahmedabad +917728919243 call me Independent Escort Service
Call Girls Ahmedabad +917728919243 call me Independent Escort Service
 
Connaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verified
Connaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verifiedConnaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verified
Connaught Place, Delhi Call girls :8448380779 Model Escorts | 100% verified
 
Conjugation, transduction and transformation
Conjugation, transduction and transformationConjugation, transduction and transformation
Conjugation, transduction and transformation
 
Proteomics: types, protein profiling steps etc.
Proteomics: types, protein profiling steps etc.Proteomics: types, protein profiling steps etc.
Proteomics: types, protein profiling steps etc.
 
PSYCHOSOCIAL NEEDS. in nursing II sem pptx
PSYCHOSOCIAL NEEDS. in nursing II sem pptxPSYCHOSOCIAL NEEDS. in nursing II sem pptx
PSYCHOSOCIAL NEEDS. in nursing II sem pptx
 
GBSN - Microbiology (Unit 2)
GBSN - Microbiology (Unit 2)GBSN - Microbiology (Unit 2)
GBSN - Microbiology (Unit 2)
 
Pests of cotton_Sucking_Pests_Dr.UPR.pdf
Pests of cotton_Sucking_Pests_Dr.UPR.pdfPests of cotton_Sucking_Pests_Dr.UPR.pdf
Pests of cotton_Sucking_Pests_Dr.UPR.pdf
 
Dubai Call Girls Beauty Face Teen O525547819 Call Girls Dubai Young
Dubai Call Girls Beauty Face Teen O525547819 Call Girls Dubai YoungDubai Call Girls Beauty Face Teen O525547819 Call Girls Dubai Young
Dubai Call Girls Beauty Face Teen O525547819 Call Girls Dubai Young
 
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 bAsymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
 
Factory Acceptance Test( FAT).pptx .
Factory Acceptance Test( FAT).pptx       .Factory Acceptance Test( FAT).pptx       .
Factory Acceptance Test( FAT).pptx .
 
Thyroid Physiology_Dr.E. Muralinath_ Associate Professor
Thyroid Physiology_Dr.E. Muralinath_ Associate ProfessorThyroid Physiology_Dr.E. Muralinath_ Associate Professor
Thyroid Physiology_Dr.E. Muralinath_ Associate Professor
 
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
 
Clean In Place(CIP).pptx .
Clean In Place(CIP).pptx                 .Clean In Place(CIP).pptx                 .
Clean In Place(CIP).pptx .
 
High Profile 🔝 8250077686 📞 Call Girls Service in GTB Nagar🍑
High Profile 🔝 8250077686 📞 Call Girls Service in GTB Nagar🍑High Profile 🔝 8250077686 📞 Call Girls Service in GTB Nagar🍑
High Profile 🔝 8250077686 📞 Call Girls Service in GTB Nagar🍑
 
chemical bonding Essentials of Physical Chemistry2.pdf
chemical bonding Essentials of Physical Chemistry2.pdfchemical bonding Essentials of Physical Chemistry2.pdf
chemical bonding Essentials of Physical Chemistry2.pdf
 
GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)
 
GBSN - Biochemistry (Unit 1)
GBSN - Biochemistry (Unit 1)GBSN - Biochemistry (Unit 1)
GBSN - Biochemistry (Unit 1)
 

Victor Zamaraev – Boundary properties of factorial classes of graphs

  • 1. Boundary properties of factorial classes of graphs Victor Zamaraev Laboratory of Algorithms and Technologies for Networks Analysis (LATNA), Higher School of Economics Joint work with Vadim Lozin, University of Warwick Workshop on Extremal Graph Theory 6 June 2014
  • 2. Boundary properties of factorial classes of graphs Introduction 2 / 28
  • 3. Boundary properties of factorial classes of graphs Introduction All considered graphs are simple (undirected, without loops and without multiple edges). 3 / 28
  • 4. Boundary properties of factorial classes of graphs Introduction All considered graphs are simple (undirected, without loops and without multiple edges). Graphs are labeled by natural numbers 1, . . . , n 6 4 5 1 2 3 3 / 28
  • 5. Boundary properties of factorial classes of graphs Introduction Definition A class is a set of graphs closed under isomorphism. 4 / 28
  • 6. Boundary properties of factorial classes of graphs Introduction Definition A class is a set of graphs closed under isomorphism. Definition A class of graphs is hereditary if it is closed under taking induced subgraphs. 4 / 28
  • 7. Boundary properties of factorial classes of graphs Introduction Definition A class is a set of graphs closed under isomorphism. Definition A class of graphs is hereditary if it is closed under taking induced subgraphs. Exapmle Let X be a hereditary class and W4 ∈ X. Then C4 ∈ X. 1 2 3 4 5 1 2 3 4 W4 C4 4 / 28
  • 8. Boundary properties of factorial classes of graphs Introduction Every hereditary graph class X can be defined by a set of forbidden induced subgraphs. 5 / 28
  • 9. Boundary properties of factorial classes of graphs Introduction Every hereditary graph class X can be defined by a set of forbidden induced subgraphs. Let M be a set of graphs. Then Free(M) denotes the set of all graphs not containing induced subgraphs isomorphic to graphs from M. 5 / 28
  • 10. Boundary properties of factorial classes of graphs Introduction Every hereditary graph class X can be defined by a set of forbidden induced subgraphs. Let M be a set of graphs. Then Free(M) denotes the set of all graphs not containing induced subgraphs isomorphic to graphs from M. Statement Class X is hereditary if and only if there exists M such that X = Free(M). We say that graphs in X are M-free. 5 / 28
  • 11. Boundary properties of factorial classes of graphs Introduction Every hereditary graph class X can be defined by a set of forbidden induced subgraphs. Let M be a set of graphs. Then Free(M) denotes the set of all graphs not containing induced subgraphs isomorphic to graphs from M. Statement Class X is hereditary if and only if there exists M such that X = Free(M). We say that graphs in X are M-free. Example For the class of bipartite graphs M is {C3, C5, C7, . . . }, i.e. B = Free(C3, C5, C7, . . . ). 5 / 28
  • 12. Boundary properties of factorial classes of graphs Introduction For a class X denote by Xn the set of n-vertex graphs from X. 6 / 28
  • 13. Boundary properties of factorial classes of graphs Introduction For a class X denote by Xn the set of n-vertex graphs from X. Example Let P be the class of all graph. |Pn| = 2(n 2) = 2n(n−1)/2 6 / 28
  • 14. Boundary properties of factorial classes of graphs Introduction For a class X denote by Xn the set of n-vertex graphs from X. Example Let P be the class of all graph. |Pn| = 2(n 2) = 2n(n−1)/2 log2 |Pn| = Θ(n2) 6 / 28
  • 15. Boundary properties of factorial classes of graphs Introduction Theorem (Alekseev V. E., 1992; Bollob´as B. and Thomason A., 1994) For every infinite hereditary class X, which is not the class of all graphs: log2 |Xn| = 1 − 1 c(X) n2 2 + o(n2 ), (1) where c(X) ∈ N is the index of class X. 7 / 28
  • 16. Boundary properties of factorial classes of graphs Introduction Theorem (Alekseev V. E., 1992; Bollob´as B. and Thomason A., 1994) For every infinite hereditary class X, which is not the class of all graphs: log2 |Xn| = 1 − 1 c(X) n2 2 + o(n2 ), (1) where c(X) ∈ N is the index of class X. (i) For c(X) > 1, log2 |Xn| = Θ(n2) 7 / 28
  • 17. Boundary properties of factorial classes of graphs Introduction Theorem (Alekseev V. E., 1992; Bollob´as B. and Thomason A., 1994) For every infinite hereditary class X, which is not the class of all graphs: log2 |Xn| = 1 − 1 c(X) n2 2 + o(n2 ), (1) where c(X) ∈ N is the index of class X. (i) For c(X) > 1, log2 |Xn| = Θ(n2) (ii) For c(X) = 1, log2 |Xn| = o(n2) 7 / 28
  • 18. Boundary properties of factorial classes of graphs Introduction Let c(X) = 1 Question What are possible rates of growth of a function log2 |Xn|? 8 / 28
  • 19. Boundary properties of factorial classes of graphs Introduction Let c(X) = 1 Question What are possible rates of growth of a function log2 |Xn|? Scheinerman E.R., Zito J. (1994) Constant classes: log2 |Xn| = Θ(1). 8 / 28
  • 20. Boundary properties of factorial classes of graphs Introduction Let c(X) = 1 Question What are possible rates of growth of a function log2 |Xn|? Scheinerman E.R., Zito J. (1994) Constant classes: log2 |Xn| = Θ(1). Polynomial classes: log2 |Xn| = Θ(log n). 8 / 28
  • 21. Boundary properties of factorial classes of graphs Introduction Let c(X) = 1 Question What are possible rates of growth of a function log2 |Xn|? Scheinerman E.R., Zito J. (1994) Constant classes: log2 |Xn| = Θ(1). Polynomial classes: log2 |Xn| = Θ(log n). Exponential classes: log2 |Xn| = Θ(n). 8 / 28
  • 22. Boundary properties of factorial classes of graphs Introduction Let c(X) = 1 Question What are possible rates of growth of a function log2 |Xn|? Scheinerman E.R., Zito J. (1994) Constant classes: log2 |Xn| = Θ(1). Polynomial classes: log2 |Xn| = Θ(log n). Exponential classes: log2 |Xn| = Θ(n). Factorial classes: log2 |Xn| = Θ(n log n). 8 / 28
  • 23. Boundary properties of factorial classes of graphs Introduction Let c(X) = 1 Question What are possible rates of growth of a function log2 |Xn|? Scheinerman E.R., Zito J. (1994) Constant classes: log2 |Xn| = Θ(1). Polynomial classes: log2 |Xn| = Θ(log n). Exponential classes: log2 |Xn| = Θ(n). Factorial classes: log2 |Xn| = Θ(n log n). All other classes are superfactorial. 8 / 28
  • 24. Boundary properties of factorial classes of graphs Introduction Let c(X) = 1 Question What are possible rates of growth of a function log2 |Xn|? Scheinerman E.R., Zito J. (1994) Constant classes: log2 |Xn| = Θ(1). Polynomial classes: log2 |Xn| = Θ(log n). Exponential classes: log2 |Xn| = Θ(n). Factorial classes: log2 |Xn| = Θ(n log n). All other classes are superfactorial. There are no intermediate growth rates between first four ranges. For exmaple, there is no hereditary class X with log2 |Xn| = Θ( √ n). 8 / 28
  • 25. Boundary properties of factorial classes of graphs Introduction Constant Polynomial Exponential Factorial layer Classes with index 1 9 / 28
  • 26. Boundary properties of factorial classes of graphs Introduction Example Constant class: Co – complete graphs (1). 10 / 28
  • 27. Boundary properties of factorial classes of graphs Introduction Example Constant class: Co – complete graphs (1). Polynomial class: E1 – graphs with at most one edge ( n 2 + 1). 10 / 28
  • 28. Boundary properties of factorial classes of graphs Introduction Example Constant class: Co – complete graphs (1). Polynomial class: E1 – graphs with at most one edge ( n 2 + 1). Exponential class: Co + Co (2n−1). 10 / 28
  • 29. Boundary properties of factorial classes of graphs Introduction Example Constant class: Co – complete graphs (1). Polynomial class: E1 – graphs with at most one edge ( n 2 + 1). Exponential class: Co + Co (2n−1). Factorial class: F – forests (nn−2 < |Fn| < n2n). 10 / 28
  • 30. Boundary properties of factorial classes of graphs Introduction Alekseev V.E. (1997) Constant classes: log2 |Xn| = Θ(1). Polynomial classes: log2 |Xn| = Θ(log n). Exponential classes: log2 |Xn| = Θ(n). Factorial classes: log2 |Xn| = Θ(n log n). All other classes are superfactorial. 11 / 28
  • 31. Boundary properties of factorial classes of graphs Introduction Alekseev V.E. (1997) Constant classes: log2 |Xn| = Θ(1). Polynomial classes: log2 |Xn| = Θ(log n). Exponential classes: log2 |Xn| = Θ(n). Factorial classes: log2 |Xn| = Θ(n log n). All other classes are superfactorial. 1 Structural characterizations were obtained for the first three layers. 2 In every of the four layers all minimal classes were found. 11 / 28
  • 32. Boundary properties of factorial classes of graphs Introduction Constant Polynomial Exponential Factorial layer Classes with index 1 12 / 28
  • 33. Boundary properties of factorial classes of graphs Introduction Balogh J., Bollob´as B., Weinreich D. (2000) Constant classes: log2 |Xn| = Θ(1). Polynomial classes: log2 |Xn| = Θ(log n). Exponential classes: log2 |Xn| = Θ(n). Factorial classes: log2 |Xn| = Θ(n log n). All other classes are superfactorial. 13 / 28
  • 34. Boundary properties of factorial classes of graphs Introduction Balogh J., Bollob´as B., Weinreich D. (2000) Constant classes: log2 |Xn| = Θ(1). Polynomial classes: log2 |Xn| = Θ(log n). Exponential classes: log2 |Xn| = Θ(n). Factorial classes: log2 |Xn| = Θ(n log n). All other classes are superfactorial. In addition 1 Characterized lower part of the factorial layer, i.e. classes with |Xn| < n(1+o(1))n. 13 / 28
  • 35. Boundary properties of factorial classes of graphs Introduction Examples of factorial classes: forests planar graphs line graphs cographs permutation graphs threshold graphs graphs of bounded vertex degree graphs of bounded clique-width et al. 14 / 28
  • 36. Boundary properties of factorial classes of graphs Introduction Problem Characterize factorial layer. 15 / 28
  • 37. Boundary properties of factorial classes of graphs Minimal superfactorial classes Minimal superfactorial classes 16 / 28
  • 38. Boundary properties of factorial classes of graphs Minimal superfactorial classes Minimal superfactorial classes Constant Polynomial Exponential Factorial Classes with index 1
  • 39. Boundary properties of factorial classes of graphs Minimal superfactorial classes Minimal superfactorial classes Constant Polynomial Exponential Factorial Classes with index 1 ? ? ? 17 / 28
  • 40. Boundary properties of factorial classes of graphs Minimal superfactorial classes Minimal superfactorial classes log2 |Xn| = Θ(n log2 n) 18 / 28
  • 41. Boundary properties of factorial classes of graphs Minimal superfactorial classes Minimal superfactorial classes log2 |Xn| = Θ(n log2 n) CB = Free(C3, C5, C6, C7, . . .) 18 / 28
  • 42. Boundary properties of factorial classes of graphs Minimal superfactorial classes Minimal superfactorial classes log2 |Xn| = Θ(n log2 n) CB = Free(C3, C5, C6, C7, . . .) Theorem (Spinrad J. P., 1995) log2 |CBn| = Θ(n log2 n) 18 / 28
  • 43. Boundary properties of factorial classes of graphs Minimal superfactorial classes Minimal superfactorial classes log2 |Xn| = Θ(n log2 n) CB = Free(C3, C5, C6, C7, . . .) Theorem (Spinrad J. P., 1995) log2 |CBn| = Θ(n log2 n) Question Is the class of chordal bipartite graphs a minimal superfactorial? 18 / 28
  • 44. Boundary properties of factorial classes of graphs Minimal superfactorial classes Minimal superfactorial classes Theorem (Dabrowski K., Lozin V.V., Zamaraev V., 2012) Let X = Free(2C4, 2C4 + e) ∩ CB. Then log2 |Xn| = Θ(n log2 n). 2C4 2C4 + e 19 / 28
  • 45. Boundary properties of factorial classes of graphs Minimal superfactorial classes Minimal superfactorial classes Theorem (Dabrowski K., Lozin V.V., Zamaraev V., 2012) Let X = Free(2C4, 2C4 + e) ∩ CB. Then log2 |Xn| = Θ(n log2 n). 2C4 2C4 + e Open question Is the class Free(2C4, 2C4 + e) ∩ CB a minimal superfactorial? 19 / 28
  • 46. Boundary properties of factorial classes of graphs Minimal superfactorial classes Minimal superfactorial classes Denote by Bk the class of (C4, C6, ..., C2k)-free bipartite graphs. 20 / 28
  • 47. Boundary properties of factorial classes of graphs Minimal superfactorial classes Minimal superfactorial classes Denote by Bk the class of (C4, C6, ..., C2k)-free bipartite graphs. Statement (follows from the results of Lazebnik F., et al., 1995) For each integer k ≥ 2, the class Bk is superfactorial. 20 / 28
  • 48. Boundary properties of factorial classes of graphs Minimal superfactorial classes Minimal superfactorial classes Denote by Bk the class of (C4, C6, ..., C2k)-free bipartite graphs. Statement (follows from the results of Lazebnik F., et al., 1995) For each integer k ≥ 2, the class Bk is superfactorial. Infinite sequence of superfactorial classes B2 ⊃ B3 ⊃ B4 . . . . 20 / 28
  • 49. Boundary properties of factorial classes of graphs Minimal superfactorial classes Minimal superfactorial classes Denote by Bk the class of (C4, C6, ..., C2k)-free bipartite graphs. Statement (follows from the results of Lazebnik F., et al., 1995) For each integer k ≥ 2, the class Bk is superfactorial. Infinite sequence of superfactorial classes B2 ⊃ B3 ⊃ B4 . . . . In this sequence there is no minimal superfactorial class. 20 / 28
  • 50. Boundary properties of factorial classes of graphs Minimal superfactorial classes Limit classes Definition Given a sequence X1 ⊇ X2 ⊇ X3 ⊇ . . . of graph classes, we will say that the sequence converges to a class X if i≥1 Xi = X. 21 / 28
  • 51. Boundary properties of factorial classes of graphs Minimal superfactorial classes Limit classes Definition Given a sequence X1 ⊇ X2 ⊇ X3 ⊇ . . . of graph classes, we will say that the sequence converges to a class X if i≥1 Xi = X. Example The sequence B2 ⊃ B3 ⊃ B4 . . . converges to the factorial class F of forests, i.e. i≥1 Bi = F. 21 / 28
  • 52. Boundary properties of factorial classes of graphs Minimal superfactorial classes Limit classes Definition Given a sequence X1 ⊇ X2 ⊇ X3 ⊇ . . . of graph classes, we will say that the sequence converges to a class X if i≥1 Xi = X. Example The sequence B2 ⊃ B3 ⊃ B4 . . . converges to the factorial class F of forests, i.e. i≥1 Bi = F. Definition A class X of graphs is a limit class (for the factorial layer) if there is a sequence of superfactorial classes converging to X. 21 / 28
  • 53. Boundary properties of factorial classes of graphs Minimal superfactorial classes Boundary classes Definition A limit class is called boundary (or minimal) if it does not properly contain any other limit class. 22 / 28
  • 54. Boundary properties of factorial classes of graphs Minimal superfactorial classes Boundary classes Definition A limit class is called boundary (or minimal) if it does not properly contain any other limit class. Theorem A finitely defined class is superfactorial if and only if it contains a boundary class. 22 / 28
  • 55. Boundary properties of factorial classes of graphs Minimal superfactorial classes Boundary classes Definition A limit class is called boundary (or minimal) if it does not properly contain any other limit class. Theorem A finitely defined class is superfactorial if and only if it contains a boundary class. Theorem The class of forests is a boundary class. 22 / 28
  • 56. Boundary properties of factorial classes of graphs Minimal superfactorial classes Are there more boundary classes? There are five more boundary classes, which can be easly obtained from the class of forests. 23 / 28
  • 57. Boundary properties of factorial classes of graphs Minimal superfactorial classes Are there more boundary classes? There are five more boundary classes, which can be easly obtained from the class of forests. Two of them are: 1 complements of forests; 2 bipartite complements of forests; 23 / 28
  • 58. Boundary properties of factorial classes of graphs Minimal superfactorial classes Are there more boundary classes? There are five more boundary classes, which can be easly obtained from the class of forests. Two of them are: 1 complements of forests; 2 bipartite complements of forests; 1 5 2 6 3 7 4 8 F 1 5 2 6 3 7 4 8 Bipartite complement of F 23 / 28
  • 59. Boundary properties of factorial classes of graphs Minimal superfactorial classes Are there more boundary classes? There are five more boundary classes, which can be easly obtained from the class of forests. Two of them are: 1 complements of forests; 2 bipartite complements of forests; 1 5 2 6 3 7 4 8 F 1 5 2 6 3 7 4 8 Bipartite complement of F Question Are there other boundary classes? 23 / 28
  • 60. Boundary properties of factorial classes of graphs Minimal superfactorial classes Lozin’s conjecture Conjecture (Lozin’s conjecture, [Lozin V.V., Mayhill C., Zamaraev V., 2011]) A hereditary graph class X is factorial if and only if at least one of the following three classes: X ∩ B, X ∩ B и X ∩ S is factorial and each of these classes is at most factorial. B – bipartite graphs B – complements of bipartite graphs S – split graphs 24 / 28
  • 61. Boundary properties of factorial classes of graphs Minimal superfactorial classes Proper boundary subclasses B2 = Free(C4) ∩ B CB = Free(C3, C5, C6, . . .) 25 / 28
  • 62. Boundary properties of factorial classes of graphs Minimal superfactorial classes Proper boundary subclasses B2 = Free(C4) ∩ B CB = Free(C3, C5, C6, . . .) superfactorial superfactorial 25 / 28
  • 63. Boundary properties of factorial classes of graphs Minimal superfactorial classes Proper boundary subclasses B2 = Free(C4) ∩ B CB = Free(C3, C5, C6, . . .) superfactorial superfactorial i≥1 Bi = F ⊂ B2 i≥1 Bi = F ⊂ CB 25 / 28
  • 64. Boundary properties of factorial classes of graphs Minimal superfactorial classes Proper boundary subclasses B2 = Free(C4) ∩ B CB = Free(C3, C5, C6, . . .) superfactorial superfactorial i≥1 Bi = F ⊂ B2 i≥1 Bi = F ⊂ CB Bi ⊆ B2, i ≥ 1 Bi CB, i ≥ 1 25 / 28
  • 65. Boundary properties of factorial classes of graphs Minimal superfactorial classes Proper boundary subclasses B2 = Free(C4) ∩ B CB = Free(C3, C5, C6, . . .) superfactorial superfactorial i≥1 Bi = F ⊂ B2 i≥1 Bi = F ⊂ CB Bi ⊆ B2, i ≥ 1 Bi CB, i ≥ 1 Definition Let X be a superfactorial class and S a boundary subclass contained in X. We say that S is a proper boundary subclass of X if there is a sequence of superfactorial subclasses of X converging to S. 25 / 28
  • 66. Boundary properties of factorial classes of graphs Minimal superfactorial classes Proper boundary subclasses Theorem There are no proper boundary subclasses of chordal bipartite graphs. 26 / 28
  • 67. Boundary properties of factorial classes of graphs Minimal superfactorial classes Proper boundary subclasses Theorem There are no proper boundary subclasses of chordal bipartite graphs. Theorem The class of forests is the only proper boundary subclass of B2. 26 / 28
  • 68. Boundary properties of factorial classes of graphs Minimal superfactorial classes Open problems Open question Find a minimal superfactorial class. 27 / 28
  • 69. Boundary properties of factorial classes of graphs Minimal superfactorial classes Open problems Open question Find a minimal superfactorial class. Open question Is the list of boundary classes we found complete? 27 / 28