arXiv stat.ML Machine Learning

Rohit Goswami (Institute IMX and Lab-COSMO, \'Ecole polytechnique f\'ed\'erale de Lausanne): Bayesian Optimization with Gaussian Processes to Accelerate Stationary Point Searches https://arxiv.org/abs/2603.10992 https://arxiv.org/pdf/2603.10992 https://arxiv.org/html/2603.10992

Xing Liu, Axel Gandy: Kernel Tests of Equivalence https://arxiv.org/abs/2603.10886 https://arxiv.org/pdf/2603.10886 https://arxiv.org/html/2603.10886

Xiaofeng Lin, Seungbae Kim, Zhuoya Li, Zachary DeSoto, Charles Fleming, Guang Cheng: ReTabSyn: Realistic Tabular Data Synthesis via Reinforcement Learning https://arxiv.org/abs/2603.10823 https://arxiv.org/pdf/2603.10823 https://arxiv.org/html/2603.10823

Reza Ghane, Danil Akhtiamov, Babak Hassibi: Dual Space Preconditioning for Gradient Descent in the Overparameterized Regime https://arxiv.org/abs/2603.10485 https://arxiv.org/pdf/2603.10485 https://arxiv.org/html/2603.10485

Han Bao, Amirreza Eshraghi, Yutong Wang: Brenier Isotonic Regression https://arxiv.org/abs/2603.10452 https://arxiv.org/pdf/2603.10452 https://arxiv.org/html/2603.10452

Simon D. Nguyen, Troy Russo, Kentaro Hoffman, Tyler H. McCormick: Adaptive Active Learning for Regression via Reinforcement Learning https://arxiv.org/abs/2603.10435 https://arxiv.org/pdf/2603.10435 https://arxiv.org/html/2603.10435

Leo Maynard-Zhang, Zhihan Xiong, Kevin Jamieson, Maryam Fazel: On The Complexity of Best-Arm Identification in Non-Stationary Linear Bandits https://arxiv.org/abs/2603.10346 https://arxiv.org/pdf/2603.10346 https://arxiv.org/html/2603.10346

Chihiro Watanabe, Jingyu Sun: MultiwayPAM: Multiway Partitioning Around Medoids for LLM-as-a-Judge Score Analysis https://arxiv.org/abs/2603.10287 https://arxiv.org/pdf/2603.10287 https://arxiv.org/html/2603.10287

Brendon J. Brewer: Bayesian Hierarchical Models and the Maximum Entropy Principle https://arxiv.org/abs/2603.10252 https://arxiv.org/pdf/2603.10252 https://arxiv.org/html/2603.10252

Tor Lattimore: A Diffusion Analysis of Policy Gradient for Stochastic Bandits https://arxiv.org/abs/2603.10219 https://arxiv.org/pdf/2603.10219 https://arxiv.org/html/2603.10219

Budhaditya Halder, Ishan Sengupta, Koustav Chowdhury, Koulik Khamaru: Stability and Robustness via Regularization: Bandit Inference via Regularized Stochastic Mirror Descent https://arxiv.org/abs/2603.10184 https://arxiv.org/pdf/2603.10184 https://arxiv.org/html/2603.10184

[2026-03-12 Thu (UTC), 11 new articles found for statML Machine Learning]

Lionel Yelibi: a-TMFG: Scalable Triangulated Maximally Filtered Graphs via Approximate Nearest Neighbors https://arxiv.org/abs/2603.09564 https://arxiv.org/pdf/2603.09564 https://arxiv.org/html/2603.09564

Nicol\'as Della Penna: What Do We Care About in Bandits with Noncompliance? BRACE: Bandits with Recommendations, Abstention, and Certified Effects https://arxiv.org/abs/2603.09532 https://arxiv.org/pdf/2603.09532 https://arxiv.org/html/2603.09532

Shion Takeno, Shogo Iwazaki: On Regret Bounds of Thompson Sampling for Bayesian Optimization https://arxiv.org/abs/2603.09276 https://arxiv.org/pdf/2603.09276 https://arxiv.org/html/2603.09276

Lei Li, Zhen Wang, Lishuo Zhang: A Generative Sampler for distributions with possible discrete parameter based on Reversibility https://arxiv.org/abs/2603.09251 https://arxiv.org/pdf/2603.09251 https://arxiv.org/html/2603.09251

Max Zhuravlev: Verifying Good Regulator Conditions for Hypergraph Observers: Natural Gradient Learning from Causal Invariance via Established Theorems https://arxiv.org/abs/2603.09067 https://arxiv.org/pdf/2603.09067 https://arxiv.org/html/2603.09067

Shinto Eguchi: Statistical Inference via Generative Models: Flow Matching and Causal Inference https://arxiv.org/abs/2603.09009 https://arxiv.org/pdf/2603.09009 https://arxiv.org/html/2603.09009

Arnaud Delaunoy: Towards Reliable Simulation-based Inference https://arxiv.org/abs/2603.08947 https://arxiv.org/pdf/2603.08947 https://arxiv.org/html/2603.08947

Roberto Tacconelli: Micro-Diffusion Compression -- Binary Tree Tweedie Denoising for Online Probability Estimation https://arxiv.org/abs/2603.08771 https://arxiv.org/pdf/2603.08771 https://arxiv.org/html/2603.08771

Ayushi Agarwal: On the Formal Limits of Alignment Verification https://arxiv.org/abs/2603.08761 https://arxiv.org/pdf/2603.08761 https://arxiv.org/html/2603.08761

Seungwoo Jeong, Heung-Il Suk: Permutation-Equivariant 2D State Space Models: Theory and Canonical Architecture for Multivariate Time Series https://arxiv.org/abs/2603.08753 https://arxiv.org/pdf/2603.08753 https://arxiv.org/html/2603.08753

[2026-03-11 Wed (UTC), 10 new articles found for statML Machine Learning]

Simon Bing, Jonas Wahl, Jakob Runge: Structural Causal Bottleneck Models https://arxiv.org/abs/2603.08682 https://arxiv.org/pdf/2603.08682 https://arxiv.org/html/2603.08682

Adam Rozzio, Rafael Athanasiades, O. Deniz Akyildiz: Momentum SVGD-EM for Accelerated Maximum Marginal Likelihood Estimation https://arxiv.org/abs/2603.08676 https://arxiv.org/pdf/2603.08676 https://arxiv.org/html/2603.08676

Saeed Asadi, Jonathan Yu-Meng Li: Generative Adversarial Regression (GAR): Learning Conditional Risk Scenarios https://arxiv.org/abs/2603.08553 https://arxiv.org/pdf/2603.08553 https://arxiv.org/html/2603.08553

Olivier Jeunen: Unifying On- and Off-Policy Variance Reduction Methods https://arxiv.org/abs/2603.08370 https://arxiv.org/pdf/2603.08370 https://arxiv.org/html/2603.08370

Hamish Flynn, Joe Watson, Ingmar Posner, Jan Peters: Posterior Sampling Reinforcement Learning with Gaussian Processes for Continuous Control: Sublinear Regret Bounds for Unbounded State Spaces https://arxiv.org/abs/2603.08287 https://arxiv.org/pdf/2603.08287 https://arxiv.org/html/2603.08287

Daniel Wang, Thang D. Bui: Beyond ReinMax: Low-Variance Gradient Estimators for Discrete Latent Variables https://arxiv.org/abs/2603.08257 https://arxiv.org/pdf/2603.08257 https://arxiv.org/html/2603.08257

Jing Jingzhe, Fan Zheyi, Szu Hui Ng, Qingpei Hu: Local Constrained Bayesian Optimization https://arxiv.org/abs/2603.07965 https://arxiv.org/pdf/2603.07965 https://arxiv.org/html/2603.07965