Papers
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
Performative Recommendation: Diversifying Content via Strategic Incentives
Itay Eilat, Nir Rosenfeld
Performative Reinforcement Learning
Debmalya Mandal, Stelios Triantafyllou, Goran Radanovic
Personalized Federated Learning under Mixture of Distributions
Yue Wu, Shuaicheng Zhang, Wenchao Yu et al.
Personalized Federated Learning with Inferred Collaboration Graphs
Rui Ye, Zhenyang Ni, Fangzhao Wu et al.
Personalized Subgraph Federated Learning
Jinheon Baek, Wonyong Jeong, Jiongdao Jin et al.
Perturbation Analysis of Neural Collapse
Tom Tirer, Haoxiang Huang, Jonathan Niles-Weed
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models
Yilun Xu, Ziming Liu, Yonglong Tian et al.
PFNs4BO: In-Context Learning for Bayesian Optimization
Samuel Müller, Matthias Feurer, Noah Hollmann et al.
Phase-aware Adversarial Defense for Improving Adversarial Robustness
Dawei Zhou, Nannan Wang, Heng Yang et al.
Phase Transitions in the Detection of Correlated Databases
Dor Elimelech, Wasim Huleihel