warsaw data science - recsys2016 quick review

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RecSys 2016 Bartłomiej Twardowski

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Page 1: Warsaw Data Science - Recsys2016 Quick Review

RecSys 2016Bartłomiej Twardowski

Page 2: Warsaw Data Science - Recsys2016 Quick Review

Quick Info

• MIT Boston,15th-19th September 2016

• 2 parallel sessions

• conference - 3d, workshops - 2d

Page 3: Warsaw Data Science - Recsys2016 Quick Review

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

Page 4: Warsaw Data Science - Recsys2016 Quick Review

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…

Page 5: Warsaw Data Science - Recsys2016 Quick Review

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…

Page 6: Warsaw Data Science - Recsys2016 Quick Review

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

Page 7: Warsaw Data Science - Recsys2016 Quick Review

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)

Page 8: Warsaw Data Science - Recsys2016 Quick Review

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)

Page 9: Warsaw Data Science - Recsys2016 Quick Review

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)

Page 10: Warsaw Data Science - Recsys2016 Quick Review

Thanks!@btwardow, Bartłomiej Twardowski