|
Spotlight
|
Wed 5:30
|
Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
Hedda Cohen Indelman · Tamir Hazan
|
|
|
Poster
|
Wed 9:00
|
Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
Hedda Cohen Indelman · Tamir Hazan
|
|
|
Poster
|
Tue 21:00
|
Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives
Da Xu · Chuanwei Ruan · Evren Korpeoglu · Sushant Kumar · Kannan Achan
|
|
|
Spotlight
|
Tue 17:30
|
Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives
Da Xu · Chuanwei Ruan · Evren Korpeoglu · Sushant Kumar · Kannan Achan
|
|
|
Spotlight
|
Thu 20:40
|
Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach
Qitian Wu · Hengrui Zhang · Xiaofeng Gao · Junchi Yan · Hongyuan Zha
|
|
|
Poster
|
Thu 21:00
|
Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach
Qitian Wu · Hengrui Zhang · Xiaofeng Gao · Junchi Yan · Hongyuan Zha
|
|
|
Spotlight
|
Tue 18:25
|
A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe · Paolo Favaro
|
|
|
Poster
|
Tue 21:00
|
A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe · Paolo Favaro
|
|
|
Spotlight
|
Thu 6:35
|
Quantum algorithms for reinforcement learning with a generative model
Daochen Wang · Aarthi Sundaram · Robin Kothari · Ashish Kapoor · Martin Roetteler
|
|
|
Poster
|
Thu 9:00
|
Quantum algorithms for reinforcement learning with a generative model
Daochen Wang · Aarthi Sundaram · Robin Kothari · Ashish Kapoor · Martin Roetteler
|
|
|
Workshop
|
Fri 9:45
|
Sequential Automated Machine Learning: Bandits-driven Exploration using a Collaborative Filtering Representation
Maxime Heuillet
|
|
|
Workshop
|
Sat 12:09
|
SVP-CF: Selection via Proxy for Collaborative Filtering Data
Noveen Sachdeva · Julian McAuley · Carole-Jean Wu
|
|
