Papers
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello et al.
Optimistic Tree Searches for Combinatorial Black-Box Optimization
Cedric Malherbe, Antoine Grosnit, Rasul Tutunov et al.
Optimizing Data Collection for Machine Learning
Rafid Mahmood, James Lucas, Jose M. Alvarez et al.
Optimizing Relevance Maps of Vision Transformers Improves Robustness
Hila Chefer, Idan Schwartz, Lior Wolf
Oracle-Efficient Online Learning for Smoothed Adversaries
Nika Haghtalab, Yanjun Han, Abhishek Shetty et al.
Oracle Inequalities for Model Selection in Offline Reinforcement Learning
Jonathan N Lee, George Tucker, Ofir Nachum et al.
Ordered Subgraph Aggregation Networks
Chendi Qian, Gaurav Rattan, Floris Geerts et al.
Order-Invariant Cardinality Estimators Are Differentially Private
Charlie Dickens, Justin Thaler, Daniel Ting
OrdinalCLIP: Learning Rank Prompts for Language-Guided Ordinal Regression
Wanhua Li, Xiaoke Huang, Zheng Zhu et al.
ORIENT: Submodular Mutual Information Measures for Data Subset Selection under Distribution Shift
Athresh Karanam, Krishnateja Killamsetty, Harsha Kokel et al.
Orthogonal Transformer: An Efficient Vision Transformer Backbone with Token Orthogonalization
Huaibo Huang, Xiaoqiang Zhou, Ran He
Oscillatory Tracking of Continuous Attractor Neural Networks Account for Phase Precession and Procession of Hippocampal Place Cells
Tianhao Chu, Zilong Ji, Junfeng Zuo et al.
OST: Improving Generalization of DeepFake Detection via One-Shot Test-Time Training
Liang Chen, Yong Zhang, Yibing Song et al.
OTKGE: Multi-modal Knowledge Graph Embeddings via Optimal Transport
Zongsheng Cao, Qianqian Xu, Zhiyong Yang et al.
Outlier-Robust Sparse Estimation via Non-Convex Optimization
Yu Cheng, Ilias Diakonikolas, Rong Ge et al.
Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions
Ilias Diakonikolas, Daniel Kane, Jasper Lee et al.
Outlier Suppression: Pushing the Limit of Low-bit Transformer Language Models
Xiuying Wei, Yunchen Zhang, Xiangguo Zhang et al.
Out-of-Distribution Detection via Conditional Kernel Independence Model
Yu Wang, Jingjing Zou, Jingyang Lin et al.
Out-of-Distribution Detection with An Adaptive Likelihood Ratio on Informative Hierarchical VAE
Yewen Li, Chaojie Wang, Xiaobo Xia et al.
Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling
Junyuan Hong, Lingjuan Lyu, Jiayu Zhou et al.
Overparameterization from Computational Constraints
Sanjam Garg, Somesh Jha, Saeed Mahloujifar et al.
P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting
Ziyi Wang, Xumin Yu, Yongming Rao et al.
PAC: Assisted Value Factorization with Counterfactual Predictions in Multi-Agent Reinforcement Learning
Hanhan Zhou, Tian Lan, Vaneet Aggarwal
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization
Sanae Lotfi, Marc Finzi, Sanyam Kapoor et al.
PaCo: Parameter-Compositional Multi-task Reinforcement Learning
Lingfeng Sun, Haichao Zhang, Wei Xu et al.