Vector Institute Heads to ICLR

April 23, 2018

2018 Blog Research 2018

April 23, 2018

In a week, Vector faculty and researchers will head to International Conference on Learning Representations (ICLR) to showcase their latest research. Here is the full list of their papers and workshops featured at this year’s conference.

 

ACCEPTED PAPERS:

Kronecker-factored Curvature Approximations for Recurrent Neural Networks

By James Martens, Jimmy Ba, Matt Johnson

POSTER: Mon Apr 30th 11:00 AM — 01:00 PM @ East Meeting level; 1,2,3.

 

Quantitatively Evaluating GANs With Divergences Proposed for Training

By Daniel Jiwoong Im, Alllan He Ma, Graham W. Taylor, Kristin Branson

POSTER: Mon Apr 30th 04:30 — 06:30 PM @ East Meeting level; 1,2,3.

 

Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches

By Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger Grosse

POSTER: Mon Apr 30th 04:30 — 06:30 PM @ East Meeting level; 1,2,3.

 

Attacking Binarized Neural Networks

By Angus Galloway, Graham W. Taylor, Medhat Moussa

POSTER: Mon Apr 30th 04:30 — 06:30 PM @ East Meeting level; 1,2,3.

 

Meta-Learning for Semi-Supervised Few-Shot Classification

By Mengye Ren, Sachin Ravi, Eleni Triantafillou, Jake Snell, Kevin Swersky, Josh B. Tenenbaum, Hugo Larochelle, Richard S. Zemel

POSTER: Tue May 1st 04:30 — 06:30 PM @ East Meeting level; 1,2,3.

 

Backpropagation through the Void: Optimizing control variates for black-box gradient estimation

By Will Grathwohl, Dami Choi, Yuhuai Wu, Geoff Roeder, David Duvenaud

POSTER: Thu May 3rd 11:00 AM — 01:00 PM @ East Meeting level; 1,2,3.

 

Understanding Short-Horizon Bias in Stochastic Meta-Optimization

By Yuhuai Wu, Mengye Ren, Renjie Liao, Roger Grosse

POSTER: Thu May 3rd 11:00 AM — 01:00 PM @ East Meeting level; 1,2,3.

 

NerveNet: Learning Structured Policy with Graph Neural Networks

By Tingwu Wang, Renjie Liao, Jimmy Ba, Sanja Fidler

POSTER: Thu May 3rd 04:30 — 06:30 PM @ East Meeting level; 1,2,3.

 

 

WORKSHOP PAPERS:

 

Predict Responsibly: Increasing Fairness by Learning to Defer

By David Madras, Toniann Pitassi, Richard Zemel

WORKSHOP: Mon Apr 30th 04:30 — 06:30 PM @ East Meeting Level 8 + 15.

 

Isolating Sources of Disentanglement in Variational Autoencoders

By Tian Qi Chen, Xuechen Li, Roger Grosse, David Duvenaud

WORKSHOP: Wed May 2nd 11:00 AM — 01:00 PM @ East Meeting Level 8 + 15.

 

Graph Partition Neural Networks for Semi-Supervised Classification

By Renjie Liao, Marc Brockschmidt, Daniel Tarlow, Alexander Gaunt, Raquel Urtasun, Richard S. Zemel

WORKSHOP: Wed May 2nd 04:30 — 06:30 PM @ East Meeting Level 8 + 15.

 

Gradient-based Optimization of Neural Network Architecture

By Will Grathwohl, Elliot Creager, Seyed Ghasemipour, Richard Zemel

WORKSHOP: Thu May 3rd 11:00 AM — 01:00 PM @ East Meeting Level 8 + 15

 

Reconstructing evolutionary trajectories of mutations in cancer

By Yulia Rubanova, Ruian Shi, Roujia Li, Jeff Wintersinger, Amit Deshwar, Nil Sahin, Quaid Morris

WORKSHOP: Thu May 3rd 11:00 AM — 01:00 PM @ East Meeting Level 8 + 15.

 

Inference in probabilistic graphical models by Graph Neural Networks

By KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard Zemel, Xaq Pitkow

WORKSHOP: Thu May 3rd 04:30 — 06:30 PM @ East Meeting Level 8 + 15

 

Leveraging Constraint Logic Programming for Neural Guided Program Synthesis

By Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William Byrd, Raquel Urtasun, Richard Zemel

WORKSHOP: Thu May 3rd 04:30 — 06:30 PM @ East Meeting Level 8 + 15

 

View full schedule

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