Poster session on gather.town at: [ protected link dropped ]
During the poster session we will have the following contributions:
Dipam Paul (Emory University ), Alankrita Tewari* (KIIT University), Jiwoong Jeong (Emory University), and Imon Banerjee (Emory University) Boosting Classification Accuracy of Fertile Sperm Cell Images leveraging cDCGAN [poster] [paper]
Harshay Shah* (Microsoft Research), Prateek Jain (Google ), and Praneeth Netrapalli (Microsoft Research) Do Input Gradients Highlight Discriminative Features? [paper] Poster session 1
Yu-Lin Tsai* (National Chiao Tung University), Chia-Yi Hsu (National Yang Ming Chiao Tung University), Chia-Mu Yu (National Chiao Tung University), and Pin-Yu Chen (IBM Research) Formalizing Generalization and Robustness of Neural Networks to Weight Perturbations [poster] [paper] Both poster sessions
Arantxa Casanova* (FAIR / Mila), Michal Drozdzal (FAIR), and Adriana Romero-Soriano (FAIR) Generating unseen complex scenes: are we there yet? [video] [poster] [paper] Poster session 1
Hubert HE Etienne* (Facebook AI) Solving moral dilemmas with AI to address the social implications of the Covid-19 crisis [video] [paper] Poster session 1
Tiffany Cai* (Columbia University), Jonathan Frankle (MIT), David Schwab (Facebook AI Research), and Ari S Morcos (FAIR) Are all negatives created equal in contrastive instance discrimination? [video] [poster] [paper] Poster session 2
Arlene E Siswanto* (MIT), Jonathan Frankle (MIT), and Michael Carbin (MIT) Examining the Role of Normalization in the Lottery Ticket Hypothesis [video] [poster] [paper] Poster session 2
Namhoon Lee* (UNIST), Philip Torr (University of Oxford), and Richard Hartley (Australian National University) Optimal mini-batch size for stochastic gradient methods [poster] [paper] Poster session 1
Camille Ballas* (Dublin City University), César Laurent (Mila, Université de Montréal), Thomas George (MILA, Université de Montréal), Nicolas Ballas (Facebook FAIR), Suzanne Little (Dublin City University, Ireland), and Pascal Vincent (Facebook FAIR & MILA Université de Montréal) Investigating Loss-modelling Pruning Criteria for Unstructured Pruning [video] [poster] [paper] Poster session 2
Samuel J Bell* (University of Cambridge) and Onno P Kampman (University of Cambridge) Ideas for machine learning from psychology's reproducibility crisis [paper]
Arlene E Siswanto* (MIT), Jonathan Frankle (MIT), and Michael Carbin (MIT) Reconciling Sparse and Structured Pruning: A Scientific Study of Block Sparsity [video] [poster] [paper] Poster session 2
Jiaxin Zhang* (Oak Ridge National Laboratory) and Victor Fung (Oak Ridge National Laboratory) Efficient Inverse Learning for Materials Design and Discovery [paper] Poster session 2
Rajiv Movva* (MIT), Jonathan Frankle (MIT), and Michael Carbin (MIT) Studying the Consistency and Composability of Lottery Ticket Pruning Masks Raj Movva [video] [poster] [paper] Poster session 2
Jessica Forde* (Brown University), A. Feder Cooper* (Cornell University), and Michael L. Littman (Brown University) Model Selection's Disparate Impact in Real-World Deep Learning Applications [poster] [paper] Both poster sessions
Saurabh Garg* (CMU), Joshua Zhanson (Carnegie Mellon University), Emilio Parisotto (Carnegie Mellon University), Adarsh Prasad (Carnegie Mellon University), Zico Kolter (Carnegie Mellon University); Sivaraman Balakrishnan (CMU), Zachary Lipton (Carnegie Mellon University), Ruslan Salakhutdinov (Carnegie Mellon University), and Pradeep Ravikumar (Carnegie Mellon University) On Proximal Policy Optimization's Heavy-tailed Gradients [video] [poster] [paper] Poster session 2
The "*" indicates people presenting the work at the poster session. In the list you can also find at which poster session they will participate.