Workshops

Spring 2017

Representation Learning

Mar 27, 2017 to Mar 31, 2017

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Monday, March 27th, 2017
9:00 am–9:20 am		Coffee and Check-In
9:20 am–9:30 am		Opening Remarks
9:30 am–10:10 am		Geometry, Optimization and Generalization in Multilayer Networks Nathan Srebro, TTI Chicago
10:10 am–10:50 am		A Non-generative Framework and Convex Relaxations for Unsupervised Learning Elad Hazan, Princeton University
10:50 am–11:20 am		Break
11:20 am–12:20 pm		Representations for Language: From Word Embeddings to Sentence Meanings Christopher Manning, Stanford University
12:20 pm–2:15 pm		Lunch
2:15 pm–3:15 pm		The Missing Signal Leon Bottou, Facebook AI Research
3:15 pm–3:45 pm		Break
3:45 pm–4:25 pm		Representations of Relationships in Images and Text Hal Daume, University of Maryland at College Park
4:30 pm–4:45 pm		Spotlight Talk: A Formalization of Representation Learning Andrej Risteski, Princeton University
4:45 pm–5:00 pm		Spotlight Talk: Semi-Random Units for Learning Neural Networks with Guarantees Bo Xie, Georgia Institute of Technology
5:00 pm–6:00 pm		Reception

Tuesday, March 28th, 2017
9:00 am–9:30 am		Coffee and Check-In
9:30 am–10:10 am		Unsupervised Discovery Through Adversarial Self-Play Rob Fergus, New York University
10:10 am–10:50 am		Learning from Unlabeled Video Kristen Grauman, University of Texas, Austin
10:50 am–11:20 am		Break
11:20 am–12:20 pm		Deep Reinforcement Learning Pieter Abbeel, UC Berkeley
12:20 pm–2:15 pm		Lunch
2:15 pm–2:55 pm		Supersizing Self-Supervision: Learning Perception and Action without Human Supervision Abhinav Gupta, Carnegie Mellon University
2:55 pm–3:35 pm		Failures of Deep Learning Shai Shalev-Shwartz, Hebrew University of Jerusalem
3:35 pm–4:10 pm		Break
4:10 pm–5:00 pm		Panel

Wednesday, March 29th, 2017
9:00 am–9:30 am		Coffee and Check-In
9:30 am–10:10 am		Continuous State Machines and Grammars for Linguistic Structure Prediction Noah Smith, University of Washington
10:10 am–10:50 am		Adversarial Perceptual Representation Learning Across Diverse Modalities and Domains Trevor Darrell, UC Berkeley
10:50 am–11:20 am		Break
11:20 am–12:20 pm		Evaluating Neural Network Representations Against Human Cognition Tom Griffiths, UC Berkeley
12:20 pm–2:15 pm		Lunch
2:15 pm–2:55 pm		Representation Learning for Reading Comprehension Russ Salakhutdinov, Carnegie Mellon University
2:55 pm–3:35 pm		Tractable Learning in Structured Probability Spaces Adnan Darwiche, UCLA
3:35 pm–4:10 pm		Break
4:10 pm–4:30 pm		Spotlight Talk: Convolutional Dictionary Learning through Tensor Factorization Furong Huang, UC Irvine
4:35 pm–4:55 pm		Spotlight Talk: How to Escape Saddle Points Efficiently Praneeth Netrapalli, Microsoft Research India

Thursday, March 30th, 2017
9:00 am–9:30 am		Coffee and Check-In
9:30 am–10:10 am		Re-Thinking Representational Learning in Robotics and Music Sham Kakade, University of Washington
10:10 am–10:50 am		Representation Learning of Grounded Language and Knowledge: with and without End-to-End Learning Yejin Choi, University of Washington
10:50 am–11:20 am		Break
11:20 am–12:20 pm		TBD Yann LeCun, New York University
12:20 pm–2:15 pm		Lunch
2:15 pm–2:55 pm		Generalization and Equilibrium in Generative Adversarial Nets (GANs) Sanjeev Arora, Princeton University
2:55 pm–3:35 pm		Provably Learning of Noisy-or Networks Rong Ge, Duke University
3:35 pm–4:10 pm		Break
4:10 pm–5:00 pm		Panel

Friday, March 31st, 2017
9:00 am–9:30 am		Coffee and Check-In
9:30 am–10:10 am		Learning Paraphrastic Representations of Natural Language Sentences Kevin Gimpel, TTI Chicago
10:10 am–10:50 am		Formation and Association of Symbolic Memories in the Brain Christos Papadimitriou, UC Berkeley
10:50 am–11:20 am		Break
11:20 am–12:20 pm		Learning Representations for Active Vision Bruno Olshausen, UC Berkeley
12:20 pm–2:15 pm		Lunch
2:15 pm–2:55 pm		Resilient Representation and Provable Generalization Dawn Song, UC Berkeley
2:55 pm–3:35 pm		Word Representation Learning without <unk> Assumptions Chris Dyer, Carnegie Mellon University
3:35 pm–4:10 pm		Break
4:10 pm–4:30 pm		Spotlight Talk: Performance Guarantees for Transferring Representations Daniel McNamara, Australian National University