Papers
Pick-to-Learn and Self-Certified Gaussian Process Approximations
Daniel Marks, Dario Paccagnan
Planning and Learning in Risk-Aware Restless Multi-Arm Bandits
Nima Akbarzadeh, Yossiri Adulyasak, Erick Delage
Poisoning Bayesian Inference via Data Deletion and Replication
Matthieu Carreau, Roi Naveiro, William N. Caballero
Policy Teaching via Data Poisoning in Learning from Human Preferences
Andi Nika, Jonathan Nöther, Debmalya Mandal et al.
posteriordb: Testing, Benchmarking and Developing Bayesian Inference Algorithms
Måns Magnusson, Jakob Torgander, Paul-Christian Bürkner et al.
Posterior Mean Matching: Generative Modeling through Online Bayesian Inference
Sebastian Salazar, Michal Kucer, Yixin Wang et al.
Post-processing for Fair Regression via Explainable SVD
Zhiqun Zuo, Ding Zhu, Mohammad Mahdi Khalili
Powerful batch conformal prediction for classification
Ulysse Gazin, Ruth Heller, Etienne Roquain et al.
Prediction-Centric Uncertainty Quantification via MMD
Zheyang Shen, Jeremias Knoblauch, Samuel Power et al.
Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models
Siyan Zhao, Daniel Mingyi Israel, Guy Van den Broeck et al.
Primal-Dual Spectral Representation for Off-policy Evaluation
Yang Hu, Tianyi Chen, Na Li et al.
Prior-Dependent Allocations for Bayesian Fixed-Budget Best-Arm Identification in Structured Bandits
Nicolas Nguyen, Imad Aouali, András György et al.
Prior-Fitted Networks Scale to Larger Datasets When Treated as Weak Learners
Yuxin Wang, Botian Jiang, Yiran Guo et al.
Privacy in Metalearning and Multitask Learning: Modeling and Separations
Maryam Aliakbarpour, Konstantina Bairaktari, Adam Smith et al.
Protein Fitness Landscape: Spectral Graph Theory Perspective
Hao Zhu, Daniel M. Steinberg, Piotr Koniusz
Provable Benefits of Task-Specific Prompts for In-context Learning
Xiangyu Chang, Yingcong Li, Muti Kara et al.
Proximal Sampler with Adaptive Step Size
Bo Yuan, Jiaojiao Fan, Jiaming Liang et al.
Pure Exploration with Feedback Graphs
Alessio Russo, Yichen Song, Aldo Pacchiano
Q-function Decomposition with Intervention Semantics for Factored Action Spaces
Junkyu Lee, Tian Gao, Elliot Nelson et al.
Q-learning for Quantile MDPs: A Decomposition, Performance, and Convergence Analysis
Jia Lin Hau, Erick Delage, Esther Derman et al.
qPOTS: Efficient Batch Multiobjective Bayesian Optimization via Pareto Optimal Thompson Sampling
Ashwin Renganathan, Kade Carlson
QuACK: A Multipurpose Queuing Algorithm for Cooperative $k$-Armed Bandits
Benjamin Howson, Sarah Lucie Filippi, Ciara Pike-Burke
Quantifying Knowledge Distillation using Partial Information Decomposition
Pasan Dissanayake, Faisal Hamman, Barproda Halder et al.
Quantifying the Optimization and Generalization Advantages of Graph Neural Networks Over Multilayer Perceptrons
Wei Huang, Yuan Cao, Haonan Wang et al.
Quantile Additive Trend Filtering
Zhi Zhang, Kyle Ritscher, OSCAR HERNAN MADRID PADILLA