Papers
ShiftAddNet: A Hardware-Inspired Deep Network
Haoran You, Xiaohan Chen, Yongan Zhang et al.
Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning
Yifan Hu, Siqi Zhang, Xin Chen et al.
Minimax Value Interval for Off-Policy Evaluation and Policy Optimization
Nan Jiang, Jiawei Huang
Interventional Few-Shot Learning
Zhongqi Yue, Hanwang Zhang, Qianru Sun et al.
Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes
Hao Chen, Lili Zheng, Raed AL Kontar et al.
Dual Instrumental Variable Regression
Krikamol Muandet, Arash Mehrjou, Si Kai Lee et al.
Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? --- A Neural Tangent Kernel Perspective
Kaixuan Huang, Yuqing Wang, Molei Tao et al.
Learning abstract structure for drawing by efficient motor program induction
Lucas Tian, Kevin Ellis, Marta Kryven et al.
Improving Policy-Constrained Kidney Exchange via Pre-Screening
Duncan McElfresh, Michael Curry, Tuomas Sandholm et al.
Weakly-Supervised Reinforcement Learning for Controllable Behavior
Lisa Lee, Ben Eysenbach, Ruslan Salakhutdinov et al.
Optimal Approximation - Smoothness Tradeoffs for Soft-Max Functions
Alessandro Epasto, Mohammad Mahdian, Vahab Mirrokni et al.
Identifying Learning Rules From Neural Network Observables
Aran Nayebi, Sanjana Srivastava, Surya Ganguli et al.
The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes
Douwe Kiela, Hamed Firooz, Aravind Mohan et al.
Optimal Lottery Tickets via Subset Sum: Logarithmic Over-Parameterization is Sufficient
Ankit Pensia, Shashank Rajput, Alliot Nagle et al.
Structured Prediction for Conditional Meta-Learning
Ruohan Wang, Yiannis Demiris, Carlo Ciliberto
Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model
Raphaël Berthier, Francis R. Bach, Pierre Gaillard
Fighting Copycat Agents in Behavioral Cloning from Observation Histories
Chuan Wen, Jierui Lin, Trevor Darrell et al.
PRANK: motion Prediction based on RANKing
Yuriy Biktairov, Maxim Stebelev, Irina Rudenko et al.
Online Robust Regression via SGD on the l1 loss
Scott Pesme, Nicolas Flammarion
Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance
Ziv Goldfeld, Kristjan Greenewald, Kengo Kato
Attention-Gated Brain Propagation: How the brain can implement reward-based error backpropagation
Isabella Pozzi, Sander Bohte, Pieter Roelfsema
Riemannian Continuous Normalizing Flows
Emile Mathieu, Maximilian Nickel
Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance
Lior Yariv, Yoni Kasten, Dror Moran et al.
Bayesian Robust Optimization for Imitation Learning
Daniel Brown, Scott Niekum, Marek Petrik