Papers
Per-Pixel Classification is Not All You Need for Semantic Segmentation
Bowen Cheng, Alex Schwing, Alexander Kirillov
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators
Anish Agarwal, Abdullah Alomar, Varkey Alumootil et al.
Personalized Federated Learning With Gaussian Processes
Idan Achituve, Aviv Shamsian, Aviv Navon et al.
Perturb-and-max-product: Sampling and learning in discrete energy-based models
Miguel Lazaro-Gredilla, Antoine Dedieu, Dileep George
Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems
Yiheng Lin, Yang Hu, Guanya Shi et al.
Perturbation Theory for the Information Bottleneck
Vudtiwat Ngampruetikorn, David J Schwab
Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL
Minshuo Chen, Yan Li, Ethan Wang et al.
PettingZoo: Gym for Multi-Agent Reinforcement Learning
J KTerry, Benjamin Black, Nathaniel Grammel et al.
Photonic Differential Privacy with Direct Feedback Alignment
Ruben Ohana, Hamlet Medina, Julien Launay et al.
Physics-Aware Downsampling with Deep Learning for Scalable Flood Modeling
Niv Giladi, Zvika Ben-Haim, Sella Nevo et al.
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling
Naoya Takeishi, Alexandros Kalousis
Pipeline Combinators for Gradual AutoML
Guillaume Baudart, Martin Hirzel, Kiran Kate et al.
Piper: Multidimensional Planner for DNN Parallelization
Jakub M Tarnawski, Deepak Narayanan, Amar Phanishayee
PiRank: Scalable Learning To Rank via Differentiable Sorting
Robin Swezey, Aditya Grover, Bruno Charron et al.
Planning from Pixels in Environments with Combinatorially Hard Search Spaces
Marco Bagatella, Miroslav Olšák, Michal Rolínek et al.
Play to Grade: Testing Coding Games as Classifying Markov Decision Process
Allen Nie, Emma Brunskill, Chris Piech
PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning
Tao Yu, Cuiling Lan, Wenjun Zeng et al.
PLUGIn: A simple algorithm for inverting generative models with recovery guarantees
Babhru Joshi, Xiaowei Li, Yaniv Plan et al.
PLUR: A Unifying, Graph-Based View of Program Learning, Understanding, and Repair
Zimin Chen, Vincent J Hellendoorn, Pascal Lamblin et al.
Pointwise Bounds for Distribution Estimation under Communication Constraints
Wei-Ning Chen, Peter Kairouz, Ayfer Ozgur
PolarStream: Streaming Object Detection and Segmentation with Polar Pillars
Qi Chen, Sourabh Vora, Oscar Beijbom
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning
Tengyang Xie, Nan Jiang, Huan Wang et al.
Policy Learning Using Weak Supervision
Jingkang Wang, Hongyi Guo, Zhaowei Zhu et al.
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses
Haipeng Luo, Chen-Yu Wei, Chung-Wei Lee
POODLE: Improving Few-shot Learning via Penalizing Out-of-Distribution Samples
Duong Le, Khoi Duc Nguyen, Khoi Nguyen et al.