Papers
Weighted Sum of Gaussian Process Latent Variable Models
James A C Odgers, Ruby Sedgwick, Chrysoula Dimitra Kappatou et al.
What Ails Generative Structure-based Drug Design: Expressivity is Too Little or Too Much?
Rafal Karczewski, Samuel Kaski, Markus Heinonen et al.
What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization
Yufeng Zhang, Fengzhuo Zhang, Zhuoran Yang et al.
When Can We Solve the Weighted Low Rank Approximation Problem in Truly Subquadratic Time?
Chenyang Li, Yingyu Liang, Zhenmei Shi et al.
When the Universe is Too Big: Bounding Consideration Probabilities for Plackett-Luce Rankings
Ben Aoki-Sherwood, Catherine Bregou, David Liben-Nowell et al.
Your copula is a classifier in disguise: classification-based copula density estimation
David Huk, Mark Steel, Ritabrata Dutta
Your Finetuned Large Language Model is Already a Powerful Out-of-distribution Detector
Andi Zhang, Tim Z. Xiao, Weiyang Liu et al.
Zero-Shot Action Generalization with Limited Observations
Abdullah Alchihabi, Hanping Zhang, Yuhong Guo
A 4-Approximation Algorithm for Min Max Correlation Clustering
Holger S. G. Heidrich, Jannik Irmai, Bjoern Andres
A Bayesian Learning Algorithm for Unknown Zero-sum Stochastic Games with an Arbitrary Opponent
Mehdi Jafarnia Jahromi, Rahul A Jain, Ashutosh Nayyar
Absence of spurious solutions far from ground truth: A low-rank analysis with high-order losses
Ziye Ma, Ying Chen, Javad Lavaei et al.
A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity
Zhihan Xiong, Romain Camilleri, Maryam Fazel et al.
A/B testing under Interference with Partial Network Information
Shiv Shankar, Ritwik Sinha, Yash Chandak et al.
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo
Haoyang Zheng, Wei Deng, Christian Moya et al.
Acceleration and Implicit Regularization in Gaussian Phase Retrieval
Tyler Maunu, Martin Molina-Fructuoso
Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex
Yasushi Esaki, Akihiro Nakamura, Keisuke Kawano et al.
Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning
Taeuk Jang, Hongchang Gao, Pengyi Shi et al.
Achieving Group Distributional Robustness and Minimax Group Fairness with Interpolating Classifiers
Natalia L. Martinez, Martin A. Bertran, Guillermo Sapiro
A Cubic-regularized Policy Newton Algorithm for Reinforcement Learning
Mizhaan P. Maniyar, Prashanth L.A., Akash Mondal et al.
Adaptive and non-adaptive minimax rates for weighted Laplacian-Eigenmap based nonparametric regression
Zhaoyang Shi, Krishna Balasubramanian, Wolfgang Polonik
Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach
Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen et al.
Adaptive Compression in Federated Learning via Side Information
Berivan Isik, Francesco Pase, Deniz Gunduz et al.
Adaptive Discretization for Event PredicTion (ADEPT)
Jimmy Hickey, Ricardo Henao, Daniel Wojdyla et al.
Adaptive Experiment Design with Synthetic Controls
Alihan Hüyük, Zhaozhi Qian, Mihaela van der Schaar
Adaptive Federated Minimax Optimization with Lower Complexities
Feihu Huang, Xinrui Wang, Junyi Li et al.