Personal Information
Organização/Local de trabalho
Paris Area, France France
Cargo
Machine learning scientist
Setor
Technology / Software / Internet
Sobre
My main research interest is in the old goal of Artificial Intelligence (AI) which is building autonomous system that can learn to be broadly competent in dynamic and uncertain environments. The field of reinforcement learning (RL) has focused on this goal, which is different from supervised learning in that correct input/output pairs are never presented. Further, there is a focus on online performance, which involves finding a balance between exploration (exploring action for increasing the knowledge about the environment) and exploitation (of current knowledge).
Marcadores
recommender system; machine learning; exploration/
mobile; machine learning; exploration/exploitation
recommender system; context
l’apprentissage automatique; l’adaptation des
learning; inference engine; ubiquitous ;recommende
evolution user intrest
traitement du langage naturel
système question réponse
reconnaissance d‟inférence textuelle
recherche d‟information
inférence temporelle
natural language processing
recognizing of textual entailment
information retrieval.
question answering system
temporal inference
recommender system
context-aware
exploration exploitation
bandit algorithm
recommender systems
hybrid-e-greedy
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Documentos
(7)Gostaram
(1)Social Recommender Systems Tutorial - WWW 2011
idoguy
•
Há 13 anos
Personal Information
Organização/Local de trabalho
Paris Area, France France
Cargo
Machine learning scientist
Setor
Technology / Software / Internet
Sobre
My main research interest is in the old goal of Artificial Intelligence (AI) which is building autonomous system that can learn to be broadly competent in dynamic and uncertain environments. The field of reinforcement learning (RL) has focused on this goal, which is different from supervised learning in that correct input/output pairs are never presented. Further, there is a focus on online performance, which involves finding a balance between exploration (exploring action for increasing the knowledge about the environment) and exploitation (of current knowledge).
Marcadores
recommender system; machine learning; exploration/
mobile; machine learning; exploration/exploitation
recommender system; context
l’apprentissage automatique; l’adaptation des
learning; inference engine; ubiquitous ;recommende
evolution user intrest
traitement du langage naturel
système question réponse
reconnaissance d‟inférence textuelle
recherche d‟information
inférence temporelle
natural language processing
recognizing of textual entailment
information retrieval.
question answering system
temporal inference
recommender system
context-aware
exploration exploitation
bandit algorithm
recommender systems
hybrid-e-greedy
Ver mais