Papers
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond
Thanh Nguyen-Tang, Raman Arora
On Separate Normalization in Self-supervised Transformers
Xiaohui Chen, Yinkai Wang, Yuanqi Du et al.
On Single-Index Models beyond Gaussian Data
Aaron Zweig, Loucas PILLAUD-VIVIEN, Joan Bruna
On skip connections and normalisation layers in deep optimisation
Lachlan MacDonald, Jack Valmadre, Hemanth Saratchandran et al.
On Slicing Optimality for Mutual Information
Ammar Fayad, Majd Ibrahim
On Sparse Modern Hopfield Model
Jerry Yao-Chieh Hu, Donglin Yang, Dennis Wu et al.
On student-teacher deviations in distillation: does it pay to disobey?
Vaishnavh Nagarajan, Aditya K Menon, Srinadh Bhojanapalli et al.
On the Ability of Graph Neural Networks to Model Interactions Between Vertices
Noam Razin, Tom Verbin, Nadav Cohen
On the Adversarial Robustness of Out-of-distribution Generalization Models
Xin Zou, Weiwei Liu
On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-law Decay
Yicheng Li, haobo Zhang, Qian Lin
On the choice of Perception Loss Function for Learned Video Compression
Sadaf Salehkalaibar, Truong Buu Phan, Jun Chen et al.
On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence
Achraf Azize, Marc Jourdan, Aymen Al Marjani et al.
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness
Vivek Ramanujan, Thao Nguyen, Sewoong Oh et al.
On the Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis
Arghya Datta, Sayak Chakrabarty
On the Constrained Time-Series Generation Problem
Andrea Coletta, Sriram Gopalakrishnan, Daniel Borrajo et al.
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $\epsilon$-Greedy Exploration
Shuai Zhang, Hongkang Li, Meng Wang et al.
On the Convergence of Black-Box Variational Inference
Kyurae Kim, Jisu Oh, Kaiwen Wu et al.
On the Convergence of CART under Sufficient Impurity Decrease Condition
Rahul Mazumder, Haoyue Wang
On the Convergence of Encoder-only Shallow Transformers
Yongtao Wu, Fanghui Liu, Grigorios Chrysos et al.
On the Convergence of No-Regret Learning Dynamics in Time-Varying Games
Ioannis Anagnostides, Ioannis Panageas, Gabriele Farina et al.
On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms
Lam Nguyen, Trang H. Tran
On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective
Mathieu Serrurier, Franck Mamalet, Thomas FEL et al.
On the Exploitability of Instruction Tuning
Manli Shu, Jiongxiao Wang, Chen Zhu et al.
On the Exploration of Local Significant Differences For Two-Sample Test
Zhijian Zhou, Jie Ni, Jia-He Yao et al.
On-the-Fly Adapting Code Summarization on Trainable Cost-Effective Language Models
Yufan Cai, Yun Lin, Chenyan Liu et al.