253 citations · 745 across the 24 of their papers we have counts for
31 papers · 1 filter
Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs
Han Zhong, Jiayi Huang, Lin F. Yang +1
Despite a large amount of effort in dealing with heavy-tailed error in machine learning, little is known when moments of the error can become non-existential: the random noise …
Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis
Jikai Jin, Bohang Zhang, Haiyang Wang +1
Distributionally robust optimization (DRO) is a widely-used approach to learn models that are robust against distribution shift. Compared with the standard optimization setting, th…
Multi-stage Optimization based Adversarial Training
Xiaosen Wang, Chuanbiao Song, Liwei Wang +1
In the field of adversarial robustness, there is a common practice that adopts the single-step adversarial training for quickly developing adversarially robust models. However, the…
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding
Shengjie Luo, Shanda Li, Tianle Cai +6
The attention module, which is a crucial component in Transformer, cannot scale efficiently to long sequences due to its quadratic complexity. Many works focus on approximating the…
Towards a Theoretical Framework of Out-of-Distribution Generalization
Haotian Ye, Chuanlong Xie, Tianle Cai +3
Generalization to out-of-distribution (OOD) data is one of the central problems in modern machine learning. Recently, there is a surge of attempts to propose algorithms that mainly…
Near-optimal Representation Learning for Linear Bandits and Linear RL
Jiachen Hu, Xiaoyu Chen, Chi Jin +2
This paper studies representation learning for multi-task linear bandits and multi-task episodic RL with linear value function approximation. We first consider the setting where we…