Papers
The Phenomenon of Policy Churn
Tom Schaul, Andre Barreto, John Quan et al.
The Pitfalls of Regularization in Off-Policy TD Learning
Gaurav Manek, J. Zico Kolter
The Policy-gradient Placement and Generative Routing Neural Networks for Chip Design
Ruoyu Cheng, Xianglong Lyu, Yang Li et al.
The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift
Jingfeng Wu, Difan Zou, Vladimir Braverman et al.
The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation?
Jean Barbier, TianQi Hou, Marco Mondelli et al.
The price of unfairness in linear bandits with biased feedback
Solenne Gaucher, Alexandra Carpentier, Christophe Giraud
The Privacy Onion Effect: Memorization is Relative
Nicholas Carlini, Matthew Jagielski, Chiyuan Zhang et al.
The Query Complexity of Cake Cutting
Simina Branzei, Noam Nisan
The Role of Baselines in Policy Gradient Optimization
Jincheng Mei, Wesley Chung, Valentin Thomas et al.
The Sample Complexity of One-Hidden-Layer Neural Networks
Gal Vardi, Ohad Shamir, Nati Srebro
Theseus: A Library for Differentiable Nonlinear Optimization
Luis Pineda, Taosha Fan, Maurizio Monge et al.
The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models
Conglong Li, Minjia Zhang, Yuxiong He
The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games
Chao Yu, Akash Velu, Eugene Vinitsky et al.
The trade-offs of model size in large recommendation models : 100GB to 10MB Criteo-tb DLRM model
Aditya Desai, Anshumali Shrivastava
The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes
Peter Kocsis, Peter Súkeník, Guillem Braso et al.
The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning
Xi Ye, Greg Durrett
Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization
Idan Amir, Roi Livni, Nati Srebro
Thinned random measures for sparse graphs with overlapping communities
Federica Zoe Ricci, Michele Guindani, Erik B. Sudderth
This is the way: designing and compiling LEPISZCZE, a comprehensive NLP benchmark for Polish
Lukasz Augustyniak, Kamil Tagowski, Albert Sawczyn et al.
Thompson Sampling Efficiently Learns to Control Diffusion Processes
Mohamad Kazem Shirani Faradonbeh, Mohamad Sadegh Shirani Faradonbeh, Mohsen Bayati
Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers
Albert Qiaochu Jiang, Wenda Li, Szymon Tworkowski et al.
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret
Jiawei Huang, Li Zhao, Tao Qin et al.
Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems
Pouria Mahdavinia, Yuyang Deng, Haochuan Li et al.
Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes
Alessio Mazzetto, Cristina Menghini, Andrew Yuan et al.
Tight Mutual Information Estimation With Contrastive Fenchel-Legendre Optimization
Qing Guo, Junya Chen, Dong Wang et al.