Papers
On the Generalization Error of Stochastic Mirror Descent for Quadratically-Bounded Losses: an Improved Analysis
Ta Duy Nguyen, Alina Ene, Huy Nguyen
On the Generalization Properties of Diffusion Models
Puheng Li, Zhong Li, Huishuai Zhang et al.
On the Gini-impurity Preservation For Privacy Random Forests
XinRan Xie, Man-Jie Yuan, Xuetong Bai et al.
On the Identifiability and Interpretability of Gaussian Process Models
Jiawen Chen, Wancen Mu, Yun Li et al.
On the Identifiability of Sparse ICA without Assuming Non-Gaussianity
Ignavier Ng, Yujia Zheng, Xinshuai Dong et al.
On the impact of activation and normalization in obtaining isometric embeddings at initialization
Amir Joudaki, Hadi Daneshmand, Francis R. Bach
On the Implicit Bias of Linear Equivariant Steerable Networks
Ziyu Chen, Wei Zhu
On the Importance of Exploration for Generalization in Reinforcement Learning
Yiding Jiang, J. Zico Kolter, Roberta Raileanu
On the Importance of Feature Separability in Predicting Out-Of-Distribution Error
RENCHUNZI XIE, Hongxin Wei, Lei Feng et al.
On the Interplay between Social Welfare and Tractability of Equilibria
Ioannis Anagnostides, Tuomas Sandholm
On the Last-iterate Convergence in Time-varying Zero-sum Games: Extra Gradient Succeeds where Optimism Fails
Yi Feng, Hu Fu, Qun Hu et al.
On the Learnability of Multilabel Ranking
Vinod Raman, UNIQUE SUBEDI, Ambuj Tewari
On the Minimax Regret for Online Learning with Feedback Graphs
Khaled Eldowa, Emmanuel Esposito, Tom Cesari et al.
On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets
Jiashuo Liu, Tianyu Wang, Peng Cui et al.
On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective
Zeke Xie, Zhiqiang Xu, Jingzhao Zhang et al.
On the Overlooked Structure of Stochastic Gradients
Zeke Xie, Qian-Yuan Tang, Mingming Sun et al.
On the Pareto Front of Multilingual Neural Machine Translation
Liang Chen, Shuming Ma, Dongdong Zhang et al.
On the Planning Abilities of Large Language Models - A Critical Investigation
Karthik Valmeekam, Matthew Marquez, Sarath Sreedharan et al.
On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection
Sangha Park, Jisoo Mok, Dahuin Jung et al.
On the Power of SVD in the Stochastic Block Model
Xinyu Mao, Jiapeng Zhang
On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions
Yufeng Zhang, Jialu Pan, Li Ken Li et al.
On the Relationship Between Relevance and Conflict in Online Social Link Recommendations
Yanbang Wang, Jon M. Kleinberg
On the Robustness of Mechanism Design under Total Variation Distance
Anuran Makur, Marios Mertzanidis, Alexandros Psomas et al.
On the Robustness of Removal-Based Feature Attributions
Chris Lin, Ian Covert, Su-In Lee
On the Role of Entanglement and Statistics in Learning
Srinivasan Arunachalam, Vojtech Havlicek, Louis Schatzki