Papers
Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations
Hanjiang Hu, Zuxin Liu, Linyi Li et al.
Policy Evaluation for Reinforcement Learning from Human Feedback: A Sample Complexity Analysis
Zihao Li, Xiang Ji, Minshuo Chen et al.
Policy Learning for Localized Interventions from Observational Data
Myrl G. Marmarelis, Fred Morstatter, Aram Galstyan et al.
Positivity-free Policy Learning with Observational Data
Pan Zhao, Antoine Chambaz, Julie Josse et al.
Posterior Uncertainty Quantification in Neural Networks using Data Augmentation
Luhuan Wu, Sinead A Williamson
Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks
Ahmad Rashid, Serena Hacker, Guojun Zhang et al.
PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model
Abhinav Chakraborty, Anirban Chatterjee, Abhinandan Dalal
Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients
Chris J. Cundy, Rishi Desai, Stefano Ermon
Privacy-Preserving Decentralized Actor-Critic for Cooperative Multi-Agent Reinforcement Learning
Maheed H. Ahmed, Mahsa Ghasemi
Private Learning with Public Features
Walid Krichene, Nicolas E Mayoraz, Steffen Rendle et al.
Probabilistic Calibration by Design for Neural Network Regression
Victor Dheur, Souhaib Ben Taieb
Probabilistic Integral Circuits
Gennaro Gala, Cassio de Campos, Robert Peharz et al.
Probabilistic Modeling for Sequences of Sets in Continuous-Time
Yuxin Chang, Alex J Boyd, Padhraic Smyth
Provable local learning rule by expert aggregation for a Hawkes network
Sophie Jaffard, Samuel Vaiter, Alexandre Muzy et al.
Provable Mutual Benefits from Federated Learning in Privacy-Sensitive Domains
Nikita Tsoy, Anna Mihalkova, Teodora N Todorova et al.
Provable Policy Gradient Methods for Average-Reward Markov Potential Games
Min Cheng, Ruida Zhou, P. R. Kumar et al.
Proving Linear Mode Connectivity of Neural Networks via Optimal Transport
Damien Ferbach, Baptiste Goujaud, Gauthier Gidel et al.
Proximal Causal Inference for Synthetic Control with Surrogates
Jizhou Liu, Eric Tchetgen Tchetgen, Carlos Varjão
Proxy Methods for Domain Adaptation
Katherine Tsai, Stephen R Pfohl, Olawale Salaudeen et al.
P-tensors: a General Framework for Higher Order Message Passing in Subgraph Neural Networks
Andrew R. Hands, Tianyi Sun, Risi Kondor
Pure Exploration in Bandits with Linear Constraints
Emil Carlsson, Debabrota Basu, Fredrik Johansson et al.
Quantifying intrinsic causal contributions via structure preserving interventions
Dominik Janzing, Patrick Blöbaum, Atalanti A Mastakouri et al.
Quantifying Uncertainty in Natural Language Explanations of Large Language Models
Sree Harsha Tanneru, Chirag Agarwal, Himabindu Lakkaraju
Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models
Frederiek Wesel, Kim Batselier