Papers
Personalized Federated Learning with Moreau Envelopes
Canh T. Dinh, Nguyen Tran, Josh Nguyen
Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach
Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability
Nathan Inkawhich, Kevin Liang, Binghui Wang et al.
Phase retrieval in high dimensions: Statistical and computational phase transitions
Antoine Maillard, Bruno Loureiro, Florent Krzakala et al.
PIE-NET: Parametric Inference of Point Cloud Edges
Xiaogang Wang, Yuelang Xu, Kai Xu et al.
Pipeline PSRO: A Scalable Approach for Finding Approximate Nash Equilibria in Large Games
Stephen Mcaleer, JB Lanier, Roy Fox et al.
Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation
Guoliang Kang, Yunchao Wei, Yi Yang et al.
PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals
Henry Charlesworth, Giovanni Montana
Planning in Markov Decision Processes with Gap-Dependent Sample Complexity
Anders Jonsson, Emilie Kaufmann, Pierre Menard et al.
Planning with General Objective Functions: Going Beyond Total Rewards
Ruosong Wang, Peilin Zhong, Simon S Du et al.
PLANS: Neuro-Symbolic Program Learning from Videos
Raphaël Dang-Nhu
PLLay: Efficient Topological Layer based on Persistent Landscapes
Kwangho Kim, Jisu Kim, Manzil Zaheer et al.
Pointer Graph Networks
Petar Veličković, Lars Buesing, Matthew Overlan et al.
Point process models for sequence detection in high-dimensional neural spike trains
Alex Williams, Anthony Degleris, Yixin Wang et al.
Policy Improvement via Imitation of Multiple Oracles
Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis
Weichao Mao, Kaiqing Zhang, Qiaomin Xie et al.
Polynomial-Time Computation of Optimal Correlated Equilibria in Two-Player Extensive-Form Games with Public Chance Moves and Beyond
Gabriele Farina, Tuomas Sandholm
POMDPs in Continuous Time and Discrete Spaces
Bastian Alt, Matthias Schultheis, Heinz Koeppl
POMO: Policy Optimization with Multiple Optima for Reinforcement Learning
Yeong-Dae Kwon, Jinho Choo, Byoungjip Kim et al.
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework
Wanxin Jin, Zhaoran Wang, Zhuoran Yang et al.
Position-based Scaled Gradient for Model Quantization and Pruning
Jangho Kim, KiYoon Yoo, Nojun Kwak
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts
Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
Posterior Re-calibration for Imbalanced Datasets
Junjiao Tian, Yen-Cheng Liu, Nathaniel Glaser et al.
Post-training Iterative Hierarchical Data Augmentation for Deep Networks
Adil Khan, Khadija Fraz