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RecSys 2016
Bartłomiej Twardowski
Quick Info
• MIT Boston,15th-19th
September 2016
• 2 parallel sessions
• conference - 3d,
workshops - 2d
Deep Learning
Paper Session 8: Deep Learning
Embedding, embedding, embedding…!
+
Meta-Prod2Vec - Product Embeddings Using Side-Information
for Recommendation
Parallel Recurrent Neural Network Architectures for Feature-
rich Session-based Recommendations
Recurrent Coevolutionary Feature Embedding Processes for
Recommendation
Workshop - RecProfile
• organized by Outbrain
• to read: Incremental Factorization Machines for
PersistentlyCold-starting Online Item
Recommendation, Takuya Kitazawa
• specific problems
• I have to listen how MF works…one more time…
Past, Present & Future
• 10 years of RecSys
• Past, Present, and Future of Recommender
Systems: An Industry Perspective, Xavier Amatriain
(Quora), Justin Basilico (Netflix)
• we will see who was right…
Contextual Cellenges
• The Contextual Turn: From Context-Aware to
Context-Driven Recommender Systems , Roberto
Pagano, et.al.
• Modeling Contextual Information in Session-Aware
Recommender Systems with Neural Networks,
Bartłomiej Twardowski
2 x Algorithms Sessions
• Local Item-Item Models For Top-N
Recommendation - Best Paper Award!
• Field-aware Factorization Machines for CTR
Prediction - nothing new :-( But at this presentation
I thought about doing intro to FM for WDS meetup.
• Using Navigation to Improve Recommendations in
Real-Time, Chao-Yuan Wu (UT Austin), Christopher
V. Alvino (Netflix), Alexander J. Smola (Carnegie
Mellon University), Justin Basilico (Netflix)
Other sessions/tutorials
• Beyond Accuracy - one of the most interesting
session
• User in the Loop
• Cold Start and Hybrid Methods
• Tutorial: Lessons Learned from Building Real-Life
Recommender Systems by Xavier Amatriain
(Quora) and Deepak Agarwal (LinkedIn)
Keynotes
• Automated Machine Learning
in the Wild by Claudia Perlich
(Dstillery)
• Personalization for Google
Now by Shashi Thakur
• Peer Effects, Social Multipliers
and Cascades of Human
Behavior by Sinan Aral (MIT)
Thanks!
@btwardow, Bartłomiej Twardowski

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Warsaw Data Science - Recsys2016 Quick Review

  • 2. Quick Info • MIT Boston,15th-19th September 2016 • 2 parallel sessions • conference - 3d, workshops - 2d
  • 3. Deep Learning Paper Session 8: Deep Learning Embedding, embedding, embedding…! + Meta-Prod2Vec - Product Embeddings Using Side-Information for Recommendation Parallel Recurrent Neural Network Architectures for Feature- rich Session-based Recommendations Recurrent Coevolutionary Feature Embedding Processes for Recommendation
  • 4. Workshop - RecProfile • organized by Outbrain • to read: Incremental Factorization Machines for PersistentlyCold-starting Online Item Recommendation, Takuya Kitazawa • specific problems • I have to listen how MF works…one more time…
  • 5. Past, Present & Future • 10 years of RecSys • Past, Present, and Future of Recommender Systems: An Industry Perspective, Xavier Amatriain (Quora), Justin Basilico (Netflix) • we will see who was right…
  • 6. Contextual Cellenges • The Contextual Turn: From Context-Aware to Context-Driven Recommender Systems , Roberto Pagano, et.al. • Modeling Contextual Information in Session-Aware Recommender Systems with Neural Networks, Bartłomiej Twardowski
  • 7. 2 x Algorithms Sessions • Local Item-Item Models For Top-N Recommendation - Best Paper Award! • Field-aware Factorization Machines for CTR Prediction - nothing new :-( But at this presentation I thought about doing intro to FM for WDS meetup. • Using Navigation to Improve Recommendations in Real-Time, Chao-Yuan Wu (UT Austin), Christopher V. Alvino (Netflix), Alexander J. Smola (Carnegie Mellon University), Justin Basilico (Netflix)
  • 8. Other sessions/tutorials • Beyond Accuracy - one of the most interesting session • User in the Loop • Cold Start and Hybrid Methods • Tutorial: Lessons Learned from Building Real-Life Recommender Systems by Xavier Amatriain (Quora) and Deepak Agarwal (LinkedIn)
  • 9. Keynotes • Automated Machine Learning in the Wild by Claudia Perlich (Dstillery) • Personalization for Google Now by Shashi Thakur • Peer Effects, Social Multipliers and Cascades of Human Behavior by Sinan Aral (MIT)