Papers
8,340 papers found
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.
PaLM-E: An Embodied Multimodal Language Model
Danny Driess, Fei Xia, Mehdi S. M. Sajjadi et al.
PAL: Program-aided Language Models
Luyu Gao, Aman Madaan, Shuyan Zhou et al.
Parallel $Q$-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation
Zechu Li, Tao Chen, Zhang-Wei Hong et al.
Parallel Neurosymbolic Integration with Concordia
Jonathan Feldstein, Modestas Jurčius, Efthymia Tsamoura
Parallel Online Clustering of Bandits via Hedonic Game
Xiaotong Cheng, Cheng Pan, Setareh Maghsudi
Parameter-Level Soft-Masking for Continual Learning
Tatsuya Konishi, Mori Kurokawa, Chihiro Ono et al.
Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models
Nikolaos Dimitriadis, Pascal Frossard, François Fleuret
Pareto Regret Analyses in Multi-objective Multi-armed Bandit
Mengfan Xu, Diego Klabjan
Partially Observable Multi-agent RL with (Quasi-)Efficiency: The Blessing of Information Sharing
Xiangyu Liu, Kaiqing Zhang
Partial Optimality in Cubic Correlation Clustering
David Stein, Silvia Di Gregorio, Bjoern Andres
PASTA: Pessimistic Assortment Optimization
Juncheng Dong, Weibin Mo, Zhengling Qi et al.
Patch-level Contrastive Learning via Positional Query for Visual Pre-training
Shaofeng Zhang, Qiang Zhou, Zhibin Wang et al.
Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks
Mohammed Nowaz Rabbani Chowdhury, Shuai Zhang, Meng Wang et al.
Path Neural Networks: Expressive and Accurate Graph Neural Networks
Gaspard Michel, Giannis Nikolentzos, Johannes F. Lutzeyer et al.
PCA-based Multi-Task Learning: a Random Matrix Approach
Malik Tiomoko, Romain Couillet, Frederic Pascal