Papers
11,015 papers found
ProxQuant: Quantized Neural Networks via Proximal Operators
Yu Bai, Yu-Xiang Wang, Edo Liberty
ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware
Han Cai, Ligeng Zhu, Song Han
Quasi-hyperbolic momentum and Adam for deep learning
Jerry Ma, Denis Yarats
Quaternion Recurrent Neural Networks
Titouan Parcollet, Mirco Ravanelli, Mohamed Morchid et al.
Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach
Minhao Cheng, Thong Le, Pin-Yu Chen et al.
Random mesh projectors for inverse problems
Konik Kothari*, Sidharth Gupta*, Maarten v. de Hoop et al.
Reasoning About Physical Interactions with Object-Oriented Prediction and Planning
Michael Janner, Sergey Levine, William T. Freeman et al.
Recall Traces: Backtracking Models for Efficient Reinforcement Learning
Anirudh Goyal, Philemon Brakel, William Fedus et al.
Recurrent Experience Replay in Distributed Reinforcement Learning
Steven Kapturowski, Georg Ostrovski, John Quan et al.
Regularized Learning for Domain Adaptation under Label Shifts
Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang et al.
Relational Forward Models for Multi-Agent Learning
Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano et al.
Relaxed Quantization for Discretized Neural Networks
Christos Louizos, Matthias Reisser, Tijmen Blankevoort et al.
RelGAN: Relational Generative Adversarial Networks for Text Generation
Weili Nie, Nina Narodytska, Ankit Patel
Representation Degeneration Problem in Training Natural Language Generation Models
Jun Gao, Di He, Xu Tan et al.
Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks
Joshua J. Michalenko, Ameesh Shah, Abhinav Verma et al.
Residual Non-local Attention Networks for Image Restoration
Yulun Zhang, Kunpeng Li, Kai Li et al.
Rethinking the Value of Network Pruning
Zhuang Liu, Mingjie Sun, Tinghui Zhou et al.
Revealing interpretable object representations from human behavior
Charles Y. Zheng, Francisco Pereira, Chris I. Baker et al.
Reward Constrained Policy Optimization
Chen Tessler, Daniel J. Mankowitz, Shie Mannor
Riemannian Adaptive Optimization Methods
Gary Becigneul, Octavian-Eugen Ganea
Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures
Jonathan Uesato*, Ananya Kumar*, Csaba Szepesvari* et al.
RNNs implicitly implement tensor-product representations
R. Thomas McCoy, Tal Linzen, Ewan Dunbar et al.
Robust Conditional Generative Adversarial Networks
Grigorios G. Chrysos, Jean Kossaifi, Stefanos Zafeiriou
ROBUST ESTIMATION VIA GENERATIVE ADVERSARIAL NETWORKS
Chao GAO, jiyi LIU, Yuan YAO et al.
Robustness May Be at Odds with Accuracy
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom et al.