Papers
Non-Convex SGD Learns Halfspaces with Adversarial Label Noise
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos et al.
Sample-Efficient Reinforcement Learning of Undercomplete POMDPs
Chi Jin, Sham Kakade, Akshay Krishnamurthy et al.
HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks
Zhen Dong, Zhewei Yao, Daiyaan Arfeen et al.
All your loss are belong to Bayes
Christian Walder, Richard Nock
Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks
Zixuan Ke, Bing Liu, Xingchang Huang
GCN meets GPU: Decoupling “When to Sample” from “How to Sample”
Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi et al.
Pre-training via Paraphrasing
Mike Lewis, Marjan Ghazvininejad, Gargi Ghosh et al.
How do fair decisions fare in long-term qualification?
Xueru Zhang, Ruibo Tu, Yang Liu et al.
Ensuring Fairness Beyond the Training Data
Debmalya Mandal, Samuel Deng, Suman Jana et al.
CoMIR: Contrastive Multimodal Image Representation for Registration
Nicolas Pielawski, Elisabeth Wetzer, Johan Öfverstedt et al.
A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices
Jiezhong Qiu, Chi Wang, Ben Liao et al.
What if Neural Networks had SVDs?
Alexander Mathiasen, Frederik Hvilshøj, Jakob Rødsgaard Jørgensen et al.
Choice Bandits
Arpit Agarwal, Nicholas Johnson, Shivani Agarwal
Batch normalization provably avoids ranks collapse for randomly initialised deep networks
Hadi Daneshmand, Jonas Kohler, Francis R. Bach et al.
What Did You Think Would Happen? Explaining Agent Behaviour through Intended Outcomes
Herman Yau, Chris Russell, Simon Hadfield
Regularizing Towards Permutation Invariance In Recurrent Models
Edo Cohen-Karlik, Avichai Ben David, Amir Globerson
BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning
Xinyue Chen, Zijian Zhou, Zheng Wang et al.
Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization
Dmitry Kovalev, Adil Salim, Peter Richtarik
BERT Loses Patience: Fast and Robust Inference with Early Exit
Wangchunshu Zhou, Canwen Xu, Tao Ge et al.
Making Non-Stochastic Control (Almost) as Easy as Stochastic
Max Simchowitz
Decentralized Accelerated Proximal Gradient Descent
Haishan Ye, Ziang Zhou, Luo Luo et al.
X-CAL: Explicit Calibration for Survival Analysis
Mark Goldstein, Xintian Han, Aahlad Puli et al.
The MAGICAL Benchmark for Robust Imitation
Sam Toyer, Rohin Shah, Andrew Critch et al.
Precise expressions for random projections: Low-rank approximation and randomized Newton
Michal Derezinski, Feynman T Liang, Zhenyu Liao et al.