Papers
Optimal Sets and Solution Paths of ReLU Networks
Aaron Mishkin, Mert Pilanci
Optimal Shrinkage for Distributed Second-Order Optimization
Fangzhao Zhang, Mert Pilanci
Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion
Ashok Cutkosky, Harsh Mehta, Francesco Orabona
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization
Sijia Chen, Wei-Wei Tu, Peng Zhao et al.
Optimistic Planning by Regularized Dynamic Programming
Antoine Moulin, Gergely Neu
Optimization for Amortized Inverse Problems
Tianci Liu, Tong Yang, Quan Zhang et al.
Optimizing DDPM Sampling with Shortcut Fine-Tuning
Ying Fan, Kangwook Lee
Optimizing Hyperparameters with Conformal Quantile Regression
David Salinas, Jacek Golebiowski, Aaron Klein et al.
Optimizing Mode Connectivity for Class Incremental Learning
Haitao Wen, Haoyang Cheng, Heqian Qiu et al.
Optimizing NOTEARS Objectives via Topological Swaps
Chang Deng, Kevin Bello, Bryon Aragam et al.
Optimizing the Collaboration Structure in Cross-Silo Federated Learning
Wenxuan Bao, Haohan Wang, Jun Wu et al.
Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning
Matthias Gerstgrasser, David C. Parkes
Orthogonality-Enforced Latent Space in Autoencoders: An Approach to Learning Disentangled Representations
Jaehoon Cha, Jeyan Thiyagalingam
Oscillation-free Quantization for Low-bit Vision Transformers
Shih-Yang Liu, Zechun Liu, Kwang-Ting Cheng
Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation
Wenqing Zheng, S P Sharan, Ajay Kumar Jaiswal et al.
Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships
Yaming Guo, Kai Guo, Xiaofeng Cao et al.
Out-of-Domain Robustness via Targeted Augmentations
Irena Gao, Shiori Sagawa, Pang Wei Koh et al.
Overcoming Simplicity Bias in Deep Networks using a Feature Sieve
Rishabh Tiwari, Pradeep Shenoy
Over-parametrization via Lifting for Low-rank Matrix Sensing: Conversion of Spurious Solutions to Strict Saddle Points
Ziye Ma, Igor Molybog, Javad Lavaei et al.
PAC-Bayesian Generalization Bounds for Adversarial Generative Models
Sokhna Diarra Mbacke, Florence Clerc, Pascal Germain
PAC-Bayesian Offline Contextual Bandits With Guarantees
Otmane Sakhi, Pierre Alquier, Nicolas Chopin
PAC Generalization via Invariant Representations
Advait U Parulekar, Karthikeyan Shanmugam, Sanjay Shakkottai
PAC Prediction Sets for Large Language Models of Code
Adam Khakhar, Stephen Mell, Osbert Bastani
Paging with Succinct Predictions
Antonios Antoniadis, Joan Boyar, Marek Elias et al.
Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions
Boxiang Lyu, Zhe Feng, Zachary Robertson et al.