Papers
Prophet Attention: Predicting Attention with Future Attention
Fenglin Liu, Xuancheng Ren, Xian Wu et al.
Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback
Zifeng Wang, Xi Chen, Rui Wen et al.
Self-Supervised Relationship Probing
Jiuxiang Gu, Jason Kuen, Shafiq Joty et al.
Outlier Robust Mean Estimation with Subgaussian Rates via Stability
Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia
On Numerosity of Deep Neural Networks
Xi Zhang, Xiaolin Wu
Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS
Han Shi, Renjie Pi, Hang Xu et al.
Ultra-Low Precision 4-bit Training of Deep Neural Networks
Xiao Sun, Naigang Wang, Chia-Yu Chen et al.
Efficient Exact Verification of Binarized Neural Networks
Kai Jia, Martin Rinard
A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees
Haoran Zhu, Pavankumar Murali, Dzung Phan et al.
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso
Jerome-Alexis Chevalier, Joseph Salmon, Alexandre Gramfort et al.
Neural Mesh Flow: 3D Manifold Mesh Generation via Diffeomorphic Flows
Kunal Gupta, Manmohan Chandraker
Deep Transformers with Latent Depth
Xian Li, Asa Cooper Stickland, Yuqing Tang et al.
Gamma-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction
Michael Janner, Igor Mordatch, Sergey Levine
Unreasonable Effectiveness of Greedy Algorithms in Multi-Armed Bandit with Many Arms
Mohsen Bayati, Nima Hamidi, Ramesh Johari et al.
Graphon Neural Networks and the Transferability of Graph Neural Networks
Luana Ruiz, Luiz Chamon, Alejandro Ribeiro
Compositional Generalization via Neural-Symbolic Stack Machines
Xinyun Chen, Chen Liang, Adams Wei Yu et al.
Locally-Adaptive Nonparametric Online Learning
Ilja Kuzborskij, Nicolò Cesa-Bianchi
Ultrahyperbolic Representation Learning
Marc Law, Jos Stam
Online Sinkhorn: Optimal Transport distances from sample streams
Arthur Mensch, Gabriel Peyré
Sinkhorn Natural Gradient for Generative Models
Zebang Shen, Zhenfu Wang, Alejandro Ribeiro et al.
On Adaptive Attacks to Adversarial Example Defenses
Florian Tramer, Nicholas Carlini, Wieland Brendel et al.
Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning
Cong Zhang, Wen Song, Zhiguang Cao et al.
Correspondence learning via linearly-invariant embedding
Riccardo Marin, Marie-Julie Rakotosaona, Simone Melzi et al.
Distribution Matching for Crowd Counting
Boyu Wang, Huidong Liu, Dimitris Samaras et al.
Neural Networks Fail to Learn Periodic Functions and How to Fix It
Liu Ziyin, Tilman Hartwig, Masahito Ueda