Saturday Morning Videos: #ICLR2017 videos

Here are the videos of this year's ICLR2017 meeting.

Monday April 24, 2017

Morning Session – Session Chair: Dhruv Batra 

Opening remarks, video starts at 12:15

9.00 - 9.40 Invited talk 1: Eero Simoncelli Elucidating and testing hierarchical sensory models through synthesis, Video starts at 26:00

9.40 - 10.00 Contributed talk 1: End-to-end Optimized Image Compression Video starts at 1:08:00

10.00 - 10.20 Contributed talk 2: Amortised MAP Inference for Image Super-resolution Video starts at 1:26:30

10.30 - 12.30 Poster Session 1 (Conference Papers, Workshop Papers)

 

h/t Libby for catching this one. From this paper.

Afternoon Session – Session Chair: Joan Bruna (sponsored by Baidu)

14.30 - 15.10 Invited talk 2: Benjamin Recht What can Deep Learning learn from linear regression Video starts at 18:30

15.10 - 15.30 Contributed Talk 3: Understanding deep learning requires rethinking generalization - BEST PAPER AWARD, Video starts at 53:30

15.30 - 15.50 Contributed Talk 4: Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima Video starts at 1;12:30

15.50 - 16.10 Contributed Talk 5: Towards Principled Methods for Training Generative Adversarial Networks Video starts at 1;30:00

16.30 - 18.30 Poster Session 2 (Conference Papers, Workshop Papers)

Tuesday April 25, 2017

Morning Session – Session Chair: Tara Sainath (sponsored by Google)

9.00 - 9.40 Invited talk 1: Chloé-Agathe Azencott High dimensional feature selection in precision medicine Video starts at 13;24
9.40 - 10.00 Contributed talk 1: Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data - BEST PAPER AWARD ,Video starts at 53:10
10.00 - 10.20 Contributed talk 2: Learning Graphical State Transitions  Video starts at 1;14;50
10.30 - 12.30 Poster Session 1 (Conference Papers, Workshop Papers)

Afternoon Session – Session Chair: Raia Hasdell (sponsored by Amazon)

14.00 - 16.00 Poster Session 2 (Conference Papers, Workshop Papers)
16.15 - 17.00 Invited talk 2: Riccardo Zecchina Video starts at 7:05
17.00 - 17.20 Contributed Talk 3: Learning to Act by Predicting the Future Video starts at 53:50
17.20 - 17.40 Contributed Talk 4: Reinforcement Learning with Unsupervised Auxiliary Tasks Video starts at 1:15:30
17.40 - 18.00 Contributed Talk 5: Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic Video starts at 1;37;10

18.00 - 18.30 Group photo at the RCT Stadium

Morning Session – Session Chair: Slav Petrov
9.00 - 9.40 Invited talk 1: Regina Barzilay Moving beyond supervised realm Video starts at 3;15 + last 8 minutes of this presentation on this video
9.40 - 10.00 Contributed talk 1: Learning End-to-End Goal-Oriented Dialog Video starts at 27:34
10.00 - 10.20 Contributed talk 2: Multi-Agent Cooperation and the Emergence of (Natural) Language Video starts at 6:00
10.30 - 12.30 Poster Session 1 (Conference Papers, Workshop Papers)

Afternoon Session – Session Chair: Navdeep Jaitly
14.30 - 15.10 Invited talk 2: Alex Graves, New Direction for Recurent Neural Networks, Video starts at 4:10

15.10 - 15.30 Contributed Talk 3: Making Neural Programming Architectures Generalize via Recursion - BEST PAPER AWARD , Video starts at 50:12

15.30 - 15.50 Contributed Talk 4: Neural Architecture Search with Reinforcement Learning Video starts at 1:08:44

15.50 - 16.10 Contributed Talk 5: Optimization as a Model for Few-Shot Learning Video starts at 1:26:30

16.30 - 18.30 Poster Session 2 (Conference Papers, Workshop Papers)

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ICLR2017, third and last day.

This is the last day of ICLR 2017. The meeting is be featured live on Facebook here at: https://www.facebook.com/iclr.cc/ . If you want to say hi, I am around.and we're hiring.


Morning Session – Session Chair: Slav Petrov
7.30 – 9.00 Registration
9.00 - 9.40 Invited talk 1: Regina Barzilay
9.40 - 10.00 Contributed talk 1: Learning End-to-End Goal-Oriented Dialog
10.00 - 10.20 Contributed talk 2: Multi-Agent Cooperation and the Emergence of (Natural) Language
10.20 - 10.30 Coffee Break
10.30 - 12.30 Poster Session 1 (Conference Papers, Workshop Papers)
12.30 - 14.30 Lunch provided by ICLR

Afternoon Session – Session Chair: Navdeep Jaitly
14.30 - 15.10 Invited talk 2: Alex Graves
15.10 - 15.30 Contributed Talk 3: Making Neural Programming Architectures Generalize via Recursion - BEST PAPER AWARD
15.30 - 15.50 Contributed Talk 4: Neural Architecture Search with Reinforcement Learning
15.50 - 16.10 Contributed Talk 5: Optimization as a Model for Few-Shot Learning
16.10 - 16.30 Coffee Break
16.30 - 18.30 Poster Session 2 (Conference Papers, Workshop Papers)

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#ICLR2017 Tuesday Afternoon Program

 

ICLR 2017 continues this afternoon in Toulon, there will be a blog post for each half day that features directly links to papers from the Open review section. The meeting will be featured live on Facebook here at: https://www.facebook.com/iclr.cc/ . If you want to say hi, I am around.and we're hiring.

 

14.00 - 16.00 Poster Session 2 (Conference Papers, Workshop Papers)
16.00 - 16.15 Coffee Break
16.15 - 17.00 Invited talk 2: Riccardo Zecchina
17.00 - 17.20 Contributed Talk 3: Learning to Act by Predicting the Future
17.20 - 17.40 Contributed Talk 4: Reinforcement Learning with Unsupervised Auxiliary Tasks
17.40 - 18.00 Contributed Talk 5: Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic
18.00 - 18.10 Group photo at the Stade Félix Mayol
19.00 - 24.00 Gala dinner offered by ICLR

C1: Sigma Delta Quantized Networks 
( code)
C2: Paleo: A Performance Model for Deep Neural Networks
C3: DeepCoder: Learning to Write Programs
C4: Topology and Geometry of Deep Rectified Network Optimization Landscapes
C5: Incremental Network Quantization: Towards Lossless CNNs with Low-precision Weights
C6: Learning to Perform Physics Experiments via Deep Reinforcement Learning
C7: Decomposing Motion and Content for Natural Video Sequence Prediction
C8: Calibrating Energy-based Generative Adversarial Networks
C9: Pruning Convolutional Neural Networks for Resource Efficient Inference
C10: Incorporating long-range consistency in CNN-based texture generation
( code )
C11: Lossy Image Compression with Compressive Autoencoders
C12: LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation
C13: Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
C14: Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data
C15: Mollifying Networks
C16: beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework
C17: Categorical Reparameterization with Gumbel-Softmax
C18: Online Bayesian Transfer Learning for Sequential Data Modeling
C19: Latent Sequence Decompositions
C20: Density estimation using Real NVP
C21: Recurrent Batch Normalization
C22: SGDR: Stochastic Gradient Descent with Restarts
C23: Variable Computation in Recurrent Neural Networks
C24: Deep Variational Information Bottleneck
C25: SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
C26: TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency
C27: Frustratingly Short Attention Spans in Neural Language Modeling
C28: Offline Bilingual Word Vectors, Orthogonal Transformations and the Inverted Softmax
C29: LEARNING A NATURAL LANGUAGE INTERFACE WITH NEURAL PROGRAMMER
C30: Designing Neural Network Architectures using Reinforcement Learning
C31: Metacontrol for Adaptive Imagination-Based Optimization (spaceship dataset )
C32: Recurrent Environment Simulators
C33: EPOpt: Learning Robust Neural Network Policies Using Model Ensembles

W1: Lifelong Perceptual Programming By Example
W2: Neu0
W3: Dance Dance Convolution
W4: Bit-Pragmatic Deep Neural Network Computing
W5: On Improving the Numerical Stability of Winograd Convolutions
W6: Fast Generation for Convolutional Autoregressive Models
W7: THE PREIMAGE OF RECTIFIER NETWORK ACTIVITIES
W8: Training Triplet Networks with GAN
W9: On Robust Concepts and Small Neural Nets
W10: Pl@ntNet app in the era of deep learning
W11: Exponential Machines
W12: Online Multi-Task Learning Using Biased Sampling
W13: Online Structure Learning for Sum-Product Networks with Gaussian Leaves
W14: A Theoretical Framework for Robustness of (Deep) Classifiers against Adversarial Samples
W15: Compositional Kernel Machines
W16: Loss is its own Reward: Self-Supervision for Reinforcement Learning
W17: REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
W18: Precise Recovery of Latent Vectors from Generative Adversarial Networks
W19: Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization (code)
 

 
 
 

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#ICLR2017 Tuesday Morning Program

 

 

 

So ICLR 2017 continues today in Toulon, there will be a blog post for each half day that features directly links to papers from the Open review section. The meeting will be featured live on Facebook here at: https://www.facebook.com/iclr.cc/ . If you want to say hi, I am around.and we're hiring.

7.30 – 9.00 Registration
9.00 - 9.40 Invited talk 1: Chloé-Agathe Azencott
9.40 - 10.00 Contributed talk 1: Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data - BEST PAPER AWARD
10.00 - 10.20 Contributed talk 2: Learning Graphical State Transitions
10.20 - 10.30 Coffee Break
10.30 - 12.30 Poster Session 1 (Conference Papers, Workshop Papers)

 Conference posters (1st floor)

 

C1: DeepDSL: A Compilation-based Domain-Specific Language for Deep Learning (code)
C2: A SELF-ATTENTIVE SENTENCE EMBEDDING
C3: Deep Probabilistic Programming
C4: Lie-Access Neural Turing Machines
C5: Learning Features of Music From Scratch
C6: Mode Regularized Generative Adversarial Networks
C7: End-to-end Optimized Image Compression (web)
C8: Variational Recurrent Adversarial Deep Domain Adaptation
C9: Steerable CNNs
C10: Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning (code)
C11: PixelVAE: A Latent Variable Model for Natural Images
C12: A recurrent neural network without chaos
C13: Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
C14: Tree-structured decoding with doubly-recurrent neural networks
C15: Introspection:Accelerating Neural Network Training By Learning Weight Evolution
C16: Hyperband: Bandit-Based Configuration Evaluation for Hyperparameter Optimization (page)
C17: Quasi-Recurrent Neural Networks (Keras)
C18: Attend, Adapt and Transfer: Attentive Deep Architecture for Adaptive Transfer from multiple sources in the same domain
C19: A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
C20: Trusting SVM for Piecewise Linear CNNs
C21: Maximum Entropy Flow Networks
C22: The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
C23: Unrolled Generative Adversarial Networks
C24: A Simple but Tough-to-Beat Baseline for Sentence Embeddings (blog entry)
C25: Query-Reduction Networks for Question Answering (code)
C26: Machine Comprehension Using Match-LSTM and Answer Pointer (code)
C27: Words or Characters? Fine-grained Gating for Reading Comprehension
C28: Dynamic Coattention Networks For Question Answering (code)
C29: Multi-view Recurrent Neural Acoustic Word Embeddings
C30: Episodic Exploration for Deep Deterministic Policies for StarCraft Micromanagement
C31: Training Agent for First-Person Shooter Game with Actor-Critic Curriculum Learning
C32: Generalizing Skills with Semi-Supervised Reinforcement Learning
C33: Improving Policy Gradient by Exploring Under-appreciated Rewards

 

3rd Floor

 

W1: Programming With a Differentiable Forth Interpreter
W2: Unsupervised Feature Learning for Audio Analysis
W3: Neural Functional Programming
W4: A Smooth Optimisation Perspective on Training Feedforward Neural Networks
W5: Synthetic Gradient Methods with Virtual Forward-Backward Networks
W6: Explaining the Learning Dynamics of Direct Feedback Alignment
W7: Training a Subsampling Mechanism in Expectation
W8: Deep Kernel Machines via the Kernel Reparametrization Trick
W9: Encoding and Decoding Representations with Sum- and Max-Product Networks
W10: Embracing Data Abundance
W11: Variational Intrinsic Control
W12: Fast Adaptation in Generative Models with Generative Matching Networks
W13: Efficient variational Bayesian neural network ensembles for outlier detection
W14: Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols
W15: Adaptive Feature Abstraction for Translating Video to Language
W16: Delving into adversarial attacks on deep policies
W17: Tuning Recurrent Neural Networks with Reinforcement Learning
W18: DeepMask: Masking DNN Models for robustness against adversarial samples
W19: Restricted Boltzmann Machines provide an accurate metric for retinal responses to visual stimuli
 

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#ICLR2017 Monday Afternoon Program

 

ICLR 2017 is taking place today in Toulon this week, there will be a blog post for each half day that features directly links to papers and attendant codes if there are any. The meeting will be featured live on Facebook here at: https://www.facebook.com/iclr.cc/ . If you want to say hi, I am around.

 

Afternoon Session – Session Chair: Joan Bruna (sponsored by Baidu) 14.30 - 15.10 Invited talk 2: Benjamin Recht
15.10 - 15.30 Contributed Talk 3: Understanding deep learning requires rethinking generalization - BEST PAPER AWARD
15.30 - 15.50 Contributed Talk 4: Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
15.50 - 16.10 Contributed Talk 5: Towards Principled Methods for Training Generative Adversarial Networks
16.10 - 16.30 Coffee Break
16.30 - 18.20 Poster Session 2 (Conference Papers, Workshop Papers)
18.20 - 18.30 Group photo at stadium attached to Neptune Congress Center.
 

C1: Neuro-Symbolic Program Synthesis
C2: Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy (code)
C3: Trained Ternary Quantization (code)
C4: DSD: Dense-Sparse-Dense Training for Deep Neural Networks (code)
C5: A Compositional Object-Based Approach to Learning Physical Dynamics (code, project site)
C6: Multilayer Recurrent Network Models of Primate Retinal Ganglion Cells
C7: Improving Generative Adversarial Networks with Denoising Feature Matching (chainer implementation)
C8: Transfer of View-manifold Learning to Similarity Perception of Novel Objects
C9: What does it take to generate natural textures?
C10: Emergence of foveal image sampling from learning to attend in visual scenes
C11: PixelCNN++: A PixelCNN Implementation with Discretized Logistic Mixture Likelihood and Other Modifications
C12: Learning to Optimize
C13: Do Deep Convolutional Nets Really Need to be Deep and Convolutional?
C14: Optimal Binary Autoencoding with Pairwise Correlations
C15: On the Quantitative Analysis of Decoder-Based Generative Models (evaluation code)
C16: Adversarial machine learning at scale
C17: Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks
C18: Capacity and Learnability in Recurrent Neural Networks
C19: Deep Learning with Dynamic Computation Graphs  (TensorFlow code)
C20: Exploring Sparsity in Recurrent Neural Networks
C21: Structured Attention Networks (code)
C22: Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learning
C23: Variational Lossy Autoencoder
C24: Learning to Query, Reason, and Answer Questions On Ambiguous Texts
C25: Deep Biaffine Attention for Neural Dependency Parsing
C26: A Compare-Aggregate Model for Matching Text Sequences (code)
C27: Data Noising as Smoothing in Neural Network Language Models
C28: Neural Variational Inference For Topic Models
C29: Bidirectional Attention Flow for Machine Comprehension (code, page)
C30: Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic
C31: Stochastic Neural Networks for Hierarchical Reinforcement Learning
C32: Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning (video)
C33: Third Person Imitation Learning

 

W1: Audio Super-Resolution using Neural Networks (code)
W2: Semantic embeddings for program behaviour patterns
W3: De novo drug design with deep generative models : an empirical study
W4: Memory Matching Networks for Genomic Sequence Classification
W5: Char2Wav: End-to-End Speech Synthesis
W6: Fast Chirplet Transform Injects Priors in Deep Learning of Animal Calls and Speech
W7: Weight-averaged consistency targets improve semi-supervised deep learning results
W8: Particle Value Functions
W9: Out-of-class novelty generation: an experimental foundation
W10: Performance guarantees for transferring representations (presentation, video)
W11: Generative Adversarial Learning of Markov Chains
W12: Short and Deep: Sketching and Neural Networks
W13: Understanding intermediate layers using linear classifier probes
W14: Symmetry-Breaking Convergence Analysis of Certain Two-layered Neural Networks with ReLU nonlinearity
W15: Neural Combinatorial Optimization with Reinforcement Learning (TensorFlow code)
W16: Tactics of Adversarial Attacks on Deep Reinforcement Learning Agents
W17: Adversarial Discriminative Domain Adaptation (workshop extended abstract)
W18: Efficient Sparse-Winograd Convolutional Neural Networks
W19: Neural Expectation Maximization 
 
 
 
 
 

Join the CompressiveSensing subreddit or the Google+ Community or the Facebook page and post there !
Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.

#ICLR2017 Monday Morning Program

 

So ICLR 2017 is taking place today in Toulon this week, there will be a blog post for each half day that features directly links to papers from the Open review section. The meeting will be featured live on Facebook here at: https://www.facebook.com/iclr.cc/ . If you want to say hi, I am around.

Monday April 24, 2017

Morning Session – Session Chair: Dhruv Batra

7.00 - 8.45 Registration
8.45 - 9.00 Opening Remarks
9.00 - 9.40 Invited talk 1: Eero Simoncelli
9.40 - 10.00 Contributed talk 1: End-to-end Optimized Image Compression
10.00 - 10.20 Contributed talk 2: Amortised MAP Inference for Image Super-resolution
10.20 - 10.30 Coffee Break
10.30 - 12.30 Poster Session 1

(Conference Papers,

C1: Making Neural Programming Architectures Generalize via Recursion (slides, code, video)
C2: Learning Graphical State Transitions (code)
C3: Distributed Second-Order Optimization using Kronecker-Factored Approximations
C4: Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes
C5: Neural Program Lattices
C6: Diet Networks: Thin Parameters for Fat Genomics
C7: Unsupervised Cross-Domain Image Generation  (TensorFlow implementation )
C8: Towards Principled Methods for Training Generative Adversarial Networks
C9: Recurrent Mixture Density Network for Spatiotemporal Visual Attention
C10: Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer (PyTorch code)
C11: Pruning Filters for Efficient ConvNets
C12: Stick-Breaking Variational Autoencoders
C13: Identity Matters in Deep Learning
C14: On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
C15: Recurrent Hidden Semi-Markov Model
C16: Nonparametric Neural Networks
C17: Learning to Generate Samples from Noise through Infusion Training
C18: An Information-Theoretic Framework for Fast and Robust Unsupervised Learning via Neural Population Infomax
C19: Highway and Residual Networks learn Unrolled Iterative Estimation
C20: Soft Weight-Sharing for Neural Network Compression (Tutorial)
C21: Snapshot Ensembles: Train 1, Get M for Free
C22: Towards a Neural Statistician
C23: Learning Curve Prediction with Bayesian Neural Networks
C24: Learning End-to-End Goal-Oriented Dialog
C25: Multi-Agent Cooperation and the Emergence of (Natural) Language
C26: Efficient Vector Representation for Documents through Corruption ( code)
C27: Improving Neural Language Models with a Continuous Cache
C28: Program Synthesis for Character Level Language Modeling
C29: Tracking the World State with Recurrent Entity Networks (TensorFlow implementation)
C30: Reinforcement Learning with Unsupervised Auxiliary Tasks (blog post, an implementation )
C31: Neural Architecture Search with Reinforcement Learning ( slides, some implementation of appendix A) 
C32: Sample Efficient Actor-Critic with Experience Replay
C33: Learning to Act by Predicting the Future

 Workshop Papers

W1: Extrapolation and learning equations (short blog post)
W2: Effectiveness of Transfer Learning in EHR data
W3: Intelligent synapses for multi-task and transfer learning
W4: Unsupervised and Efficient Neural Graph Model with Distributed Representations
W5: Accelerating SGD for Distributed Deep-Learning Using an Approximted Hessian Matrix
W6: Accelerating Eulerian Fluid Simulation With Convolutional Networks (FluidNet code)
W7: Forced to Learn: Discovering Disentangled Representations Without Exhaustive Labels
W8: Dataset Augmentation in Feature Space
W9: Learning Algorithms for Active Learning
W10: Reinterpreting Importance-Weighted Autoencoders
W11: Robustness to Adversarial Examples through an Ensemble of Specialists
W12: (empty)
W13: On Hyperparameter Optimization in Learning Systems
W14: Recurrent Normalization Propagation
W15: Joint Training of Ratings and Reviews with Recurrent Recommender Networks
W16: Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses
W17: Joint Embeddings of Scene Graphs and Images
W18: Unseen Style Transfer Based on a Conditional Fast Style Transfer Network 

 
 
 
 

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The ICLR2017 program is out

ICLR2017 just released their program ( the open review for the Workshop site is open and here)

Monday April 24, 2017

Morning Session

8.45 - 9.00 Opening Remarks

9.00 - 9.40 Invited talk 1: Eero Simoncelli

9.40 - 10.00 Contributed talk 1: End-to-end Optimized Image Compression

10.00 - 10.20 Contributed talk 2: Amortised MAP Inference for Image Super-resolution

10.00 - 10.30 Coffee Break

10.30 - 12.30 Poster Session 1

12.30 - 14.30 Lunch provided by ICLR

Afternoon Session

14.30 - 15.10 Invited talk 2: Benjamin Recht

15.10 - 15.30 Contributed Talk 3: Understanding deep learning requires rethinking generalization - BEST PAPER AWARD

15.30 - 15.50 Contributed Talk 4: Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima

15.50 - 16.10 Contributed Talk 5: Towards Principled Methods for Training Generative Adversarial Networks

16.10 - 16.30 Coffee Break

16.30 - 18.30 Poster Session 2

Tuesday April 25, 2017

Afternoon Session

9.00 - 9.40 Invited talk 1: Chloe Azencott

9.40 - 10.00 Contributed talk 1: Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data - BEST PAPER AWARD

10.00 - 10.20 Contributed talk 2: Learning Graphical State Transitions

10.20 - 10.30 Coffee Break

10.30 - 12.30 Poster Session 1

12.30 - 14.30 Lunch provided by ICLR

Afternoon Session

14.30 - 15.10 Invited talk 2: Riccardo Zecchina

15.10 - 15.30 Contributed Talk 3: Learning to Act by Predicting the Future

15.30 - 15.50 Contributed Talk 4: Reinforcement Learning with Unsupervised Auxiliary Tasks

15.50 - 16.10 Contributed Talk 5: Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic

16.10 - 16.30 Coffee Break

16.30 - 18.30 Poster Session 2

19.00 - 21.00 Gala dinner offered by ICLR

Wednesday April 26, 2017

Morning Session

9.00 - 9.40 Invited talk 1: Regina Barzilay

9.40 - 10.00 Contributed talk 1: Learning End-to-End Goal-Oriented Dialog

10.00 - 10.20 Contributed talk 2: Multi-Agent Cooperation and the Emergence of (Natural) Language

10.00 - 10.30 Coffee Break

10.30 - 12.30 Poster Session 1

12.30 - 14.30 Lunch provided by ICLR

Afternoon Session

14.30 - 15.10 Invited talk 2: Alex Graves

15.10 - 15.30 Contributed Talk 3: Making Neural Programming Architectures Generalize via Recursion - BEST PAPER AWARD

15.30 - 15.50 Contributed Talk 4: Neural Architecture Search with Reinforcement Learning

15.50 - 16.10 Contributed Talk 5: Optimization as a Model for Few-Shot Learning

16.10 - 16.30 Coffee Break

16.30 - 18.30 Poster Session 2

Credit photo: Par BaptisteMPM — Travail personnel, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=37629070


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ICLR 2017 workshop track open review

The list of accepted and rejected papers as well as papers invited to the ICLR 2017 workshop track is now here. 
Deadline submission for the ICLR workshop track is today at 5PM EST. The current stack of submission is as follows: 

Online Multi-Task Learning Using Biased SamplingSahil Sharma, Balaraman Ravindran17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesAdapting Distance Kernel to Domain adaptation for sentimental analysis Saerom Park, Jaewook Lee, Woojin Lee17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
On Improving the Numerical Stability of Winograd Convolutions
Kevin Vincent, Kevin Stephano, Michael Frumkin, Boris Ginsburg, Julien Demouth
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Fast Generation for Convolutional Autoregressive Models
Prajit Ramachandran, Tom Le Paine, Pooya Khorrami, Mohammad Babaeizadeh, Shiyu Chang, Yang Zhang, Mark A. Hasegawa-Johnson, Roy H. Campbell, Thomas S. Huang
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Online Structure Learning for Sum-Product Networks with Gaussian Leaves
Wilson Hsu, Agastya Kalra, Pascal Poupart
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Similarity preserving compressions of high dimensional sparse data
Raghav Kulkarni, Rameshwar Pratap
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses
Ryan Lowe, Michael Noseworthy, Iulian V. Serban, Nicholas Angelard-Gontier, Yoshua Bengio, Joelle Pineau
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
A Theoretical Framework for Robustness of (Deep) Classifiers against Adversarial Samples
Beilun Wang, Ji Gao, Yanjun Qi
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Factorization tricks for LSTM networks
Oleksii Kuchaiev, Boris Ginsburg
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Exploring LOTS in Deep Neural Networks
Andras Rozsa, Manuel Gunther, Terrance E. Boult
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Shake-Shake regularization of 3-branch residual networks
Xavier Gastaldi
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Trace Norm Regularised Deep Multi-Task Learning
Yongxin Yang, Timothy M. Hospedales
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Deep Learning with Sets and Point Clouds
Siamak Ravanbakhsh, Jeff Schneider, Barnabas Poczos
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
INCREMENTAL LEARNING WITH PRE-TRAINED CONVOLUTIONAL NEURAL NETWORKS AND BINARY ASSOCIATIVE MEMORIES
Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Mattieu Arzel, Michel Jezequel
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Dataset Augmentation in Feature Space
Terrance DeVries, Graham W. Taylor
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Evaluating Dimensionality Reduction of 2D Histogram Data from Truck On-board Sensors
Evaldas Vaiciukynas, Matej Ulicny, Sepideh Pashami, Slawomir Nowaczyk
17 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
NEUROGENESIS-INSPIRED DICTIONARY LEARNING: ONLINE MODEL ADAPTION IN A CHANGING WORLD
Sahil Garg, Irina Rish, Guillermo Cecchi, Aurelie Lozano
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
Class-based Prediction Errors to Categorize Text with Out-of-vocabulary Words
Joan Serrà, Ilias Leontiadis, Dimitris Spathis, Gianluca Stringhini, Jeremy Blackburn
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Delving Into Adversarial Attacks on Deep Policies
Jernej Kos, Dawn Song
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Annealed Generative Adversarial Networks
Arash Mehrjou, Saeed Saremi
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Learning a Metric for Relational Data
Jiajun Pan, Hoel Le Capitaine, Philippe Leray
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
The High-Dimensional Geometry of Binary Neural Networks
Alexander G. Anderson, Cory P. Berg
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Discovering objects and their relations from entangled scene representations
D. Raposo, A. Santoro, D.G.T. Barrett, R. Pascanu, T. Lillicrap, P. Battaglia
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Multiplicative LSTM for sequence modelling
Ben Krause, Iain Murray, Steve Renals, Liang Lu
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Learning to Discover Sparse Graphical Models
Eugene Belilovsky, Kyle Kastner, Gael Varoquaux, Matthew B. Blaschko
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
A Differentiable Physics Engine for Deep Learning in Robotics
Jonas Degrave, Michiel Hermans, Joni Dambre, Francis wyffels
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Revisiting Batch Normalization For Practical Domain Adaptation
Yanghao Li, Naiyan Wang, Jianping Shi, Jiaying Liu, Xiaodi Hou
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Coupling Distributed and Symbolic Execution for Natural Language Queries
Lili Mou, Zhengdong Lu, Hang Li, Zhi Jin
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Transferring Knowledge to Smaller Network with Class-Distance Loss
Seung Wook Kim, Hyo-Eun Kim
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Automated Generation of Multilingual Clusters for the Evaluation of Distributed Representations
Philip Blair, Yuval Merhav, Joel Barry
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently
Muthuraman Chidambaram, Yanjun Qi
16 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Infinite Dimensional Word Embeddings
Eric Nalisnick, Sachin Ravi
15 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Regularizing Neural Networks by Penalizing Confident Output Distributions
Gabriel Pereyra, George Tucker, Jan Chorowski, Lukasz Kaiser, Geoffrey Hinton
15 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
Precise Recovery of Latent Vectors from Generative Adversarial Networks
Zachary C. Lipton, Subarna Tripathi
15 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Non-Associative Learning Representation in the Nervous System of the Nematode Caenorhabditis elegans
Ramin M. Hasani, Magdalena Fuchs, Victoria Beneder, Radu Grosu
15 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
Xun Huang, Serge Belongie
15 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Recurrent Normalization Propagation
César Laurent, Nicolas Ballas, Pascal Vincent
15 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Deep Adversarial Gaussian Mixture Auto-Encoder for Clustering
Warith Harchaoui, Pierre-Alexandre Mattei, Charles Bouveyron
15 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Adversarial Examples for Semantic Image Segmentation
Volker Fischer, Mummadi Chaithanya Kumar, Jan Hendrik Metzen, Thomas Brox
15 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
RenderGAN: Generating Realistic Labeled Data
Leon Sixt, Benjamin Wild, Tim Landgraf
15 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Tuning Recurrent Neural Networks with Reinforcement Learning
Natasha Jaques, Shixiang Gu, Richard E. Turner, Douglas Eck
14 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Generalization to new compositions of known entities in image understanding
Yuval Atzmon, Jonathan Berant, Amir Globerson, Vahid Kazemi, Gal Chechik
14 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Adaptive Feature Abstraction for Translating Video to Language
Yunchen Pu, Martin Renqiang Min, Zhe Gan, Lawrence Carin
14 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Generalizable Features From Unsupervised Learning
Mehdi Mirza, Aaron Courville, Yoshua Bengio
14 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Neural Style Representations of Fine Art
Jeremiah Johnson
14 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Exploring loss function topology with cyclical learning rates
Leslie N. Smith, Nicholay Topin
14 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Compact Embedding of Binary-coded Inputs and Outputs using Bloom Filters
Joan Serrà, Alexandros Karatzoglou
13 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
Perception Updating Networks: On architectural constraints for interpretable video generative models
Decoupled "what" and "where" variational statistical framework and equivalent multi-stream network
12 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Semi-supervised deep learning by metric embedding
Elad Hoffer, Nir Ailon
11 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker, Andriy Mnih, Chris J. Maddison, Jascha Sohl-Dickstein
11 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Adversarial examples in the physical world
Alexey Kurakin, Ian J. Goodfellow, Samy Bengio
11 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Variational Reference Priors
Eric Nalisnick, Padhraic Smyth
9 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Development of JavaScript-based deep learning platform and application to distributed training
Masatoshi Hidaka, Ken Miura, Tatsuya Harada
9 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Song From PI: A Musically Plausible Network for Pop Music Generation
Hang Chu, Raquel Urtasun, Sanja Fidler
8 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Gated Multimodal Units for Information Fusion
John Arevalo, Thamar Solorio, Manuel Montes-y-Gómez, Fabio A. González
8 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Adjusting for Dropout Variance in Batch Normalization and Weight Initialization
Dan Hendrycks, Kevin Gimpel
7 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
Methods for Detecting Adversarial Images and a Colorful Saliency Map
Dan Hendrycks, Kevin Gimpel
7 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Charged Point Normalization: An Efficient Solution to the Saddle Point Problem
Armen Aghajanyan
7 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
Compositional Kernel Machines
Robert Gens, Pedro Domingos
7 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 RepliesOriginal
ICLR 2017 Conference Invite to Workshop
DL-gleaning: An approach for Improving inference speed and accuracy
HyunYong Lee and Byung-Tak Lee
6 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Towards "AlphaChem": Chemical Synthesis Planning with Tree Search and Deep Neural Network Policies
Marwin Segler, Mike Preuß, Mark P. Waller
2 Feb 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
CommAI: Evaluating the first steps towards a useful general AI
Marco Baroni, Armand Joulin, Allan Jabri, Germàn Kruszewski, Angeliki Lazaridou, Klemen Simonic, Tomas Mikolov
31 Jan 2017ICLR 2017 workshop submissionreaders: everyone0 Replies
Summarized Behavioral Prediction
Shih-Chieh Su
20 Jan 2017ICLR 2017 workshop submissionreaders: everyone0 Replies

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