Hugo mentioned it on his twitter feed, the videos of ICLRs are out. The papers are listed here.
Opening Remarks
06:43 Opening, Hugo Larochelle
Keynote Talks
Best Paper Awards
Lectures
Opening Remarks
06:43 Opening, Hugo Larochelle
Keynote Talks
- 35:37 Keynote TalkDeep Robotic Learning, Sergey Levine
- 34:34 Keynote TalkShould Model Architecture Reflect Linguistic Structure?, Chris Dyer
- 39:39 Keynote TalkGuaranteed Non-convex Learning Algorithms through Tensor Factorization, Animashree Anandkumar
- 39:29 Keynote Talk Beyond Backpropagation: Uncertainty Propagation, Neil D. Lawrence
- 39:17 Keynote TalkIncorporating Structure in Deep Learning, Raquel Urtasun
Best Paper Awards
- 15:35 Best PaperNeural Programmer-Interpreters, Scott Reed
- 17:19 Best PaperDeep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding, Song Han
Lectures
- 16:19 Regularizing RNNs by Stabilizing Activations, David Scott Krueger
- 17:11 BlackOut: Speeding up Recurrent Neural Network Language Models With Very Large Vocabularies, Shihao Ji
- 16:08 The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations, Felix Hill
- 17:29 Towards Universal Paraphrastic Sentence Embeddings, John Wieting
- 19:18 Convergent Learning: Do different neural networks learn the same representations?, Jason Yosinski
- 15:52 Net2Net: Accelerating Learning via Knowledge Transfer, Tianqi Chen
- 16:19 Variational Gaussian Process, Dustin Tran
- 15:16 The Variational Fair Autoencoder, Christos Louizos
- 16:47 A note on the evaluation of generative models, Lucas Theis
- 10:35 Neural Networks with Few Multiplications, Zhouhan Lin
- 15:55 Order-Embeddings of Images and Language, Ivan Vendrov
- 12:33 Generating Images from Captions with Attention, Elman Mansimov
- 18:34 Density Modeling of Images using a Generalized Normalization Trnsformation, Johannes Ballé
Credits: NASA/JHUAPL/SwRI
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