Machine Learning

Authors and titles for recent submissions

• Fri, 9 Oct 2026
• Thu, 8 Oct 2026
• Wed, 7 Oct 2026
• Tue, 6 Oct 2026
• Mon, 5 Oct 2026

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Fri, 9 Oct 2026 (showing first 50 of 51 entries )

[1] arXiv:2610.12437 [pdf, html, other]

Title: Density Ratio Estimation with Stein Displacement Fields

Song Liu

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[2] arXiv:2610.12332 [pdf, html, other]

Title: Prediction-Powered Data Fusion for Treatment Effect Estimation

Yonghan Jung, Shu Yang

Comments: 35 pages. Code: this https URL

Subjects: Machine Learning (stat.ML); Artificial Intelligence (cs.AI); Machine Learning (cs.LG); Methodology (stat.ME)

[3] arXiv:2610.12288 [pdf, html, other]

Title: Testing Algebraic Complete Intersections

Alessandro Tamai

Subjects: Machine Learning (stat.ML); Algebraic Geometry (math.AG); Differential Geometry (math.DG); Statistics Theory (math.ST)

[4] arXiv:2610.12213 [pdf, html, other]

Title: ISBO: Scalable Spatio-Temporal Bayesian Optimization with Log Gaussian Cox Process Models via the INLA-SPDE Approach

Kaichuang Yang, Håvard Rue, Jakob Zeitler

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[5] arXiv:2610.12200 [pdf, html, other]

Title: Quickest Change Detection with Diffusion-Integrated Scores

Arman Adibi, Mohammadreza Maleki, Sanjeev Kulkarni, H. Vincent Poor

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[6] arXiv:2610.12094 [pdf, html, other]

Title: Differentiable Systematic Resampling for Variational Sequential Monte Carlo

Fredrik Cumlin, Saikat Chatterjee

Comments: Accepted to NeurIPS 2026

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Signal Processing (eess.SP)

[7] arXiv:2610.12052 [pdf, html, other]

Title: Diffusion Removes Langevin's Conditioning Dependence: A Sharp Gaussian Analysis

Adam Perbost, Francis Bach, Pierre Marion

Comments: 49 pages (10 main + appendix), 3 figures

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[8] arXiv:2610.12035 [pdf, html, other]

Title: Efficient and Generalizable Archetypal Analysis for Discrete Data

A. Emilie J. Wedenborg, Jesper Løve Hinrich, Morten Mørup

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[9] arXiv:2610.11976 [pdf, html, other]

Title: Efficient quadratic entropy with distance sketches

Steve Huntsman

Comments: Code for reproducing results in LaTeX comments

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Statistics Theory (math.ST); Computation (stat.CO)

[10] arXiv:2610.11947 [pdf, html, other]

Title: Score-Based Learning of Cluster DAGs from Interventions

Gaetano Tedesco, Alex Markham

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[11] arXiv:2610.11906 [pdf, html, other]

Title: RobustLDS: Learning linear dynamical systems under adversarial corruptions

Aravinda Kanchana Ruwanpathirana, Hemant Tyagi

Comments: 40 pages, 8 figures

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Systems and Control (eess.SY); Optimization and Control (math.OC); Statistics Theory (math.ST)

[12] arXiv:2610.11869 [pdf, html, other]

Title: Learning structured linear dynamical systems from missing observations

Aravinda Kanchana Ruwanpathirana, Hemant Tyagi, Sunny G.W. Wang

Comments: 62 pages, 3 figures

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Systems and Control (eess.SY); Optimization and Control (math.OC); Statistics Theory (math.ST)

[13] arXiv:2610.11863 [pdf, html, other]

Title: Conditional Kernel Stein Discrepancy

Federico Matteucci, Florian Kalinke

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Statistics Theory (math.ST)

[14] arXiv:2610.11798 [pdf, other]

Title: Softmax Attention on Gaussian Mixtures: Linear When It Can, Selective When It Must

Simon Gabet (LMO), Etienne Boursier (LMO, CELESTE), Claire Boyer (LMO, IUF)

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[15] arXiv:2610.11668 [pdf, html, other]

Title: $σ$Transfer: Uncertainty Transfer from Small to Large Networks under $μ\mathrm{P}$

Richard Bergna (1 and 2), Fernando Ruiz Mazo (1), Nicolò Felicioni (2), José Miguel Hernández-Lobato (1), Kamil Ciosek (2) ((1) University of Cambridge, (2) Spotify)

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[16] arXiv:2610.11628 [pdf, html, other]

Title: Minimax Gaussian Mechanisms for Continual Machine Unlearning

Qi Kuang, Yin Xia

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[17] arXiv:2610.11584 [pdf, html, other]

Title: Embedding-Bias in Conditional Independence Testing

Nikolaj Thams, Anton Rask Lundborg

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[18] arXiv:2610.11538 [pdf, html, other]

Title: LAIR-Net: Leaky Alignment-Impulse Residual Networks for Tabular Regression

Rahul Goswami, Aryan Bhambu, Bittu Karmakar

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[19] arXiv:2610.11486 [pdf, html, other]

Title: PSI-SINDy: Post-Selection Inference for Sparse Identification of Nonlinear Dynamics

Ashraful Islam, Shuichi Nishino, Tomohiro Shiraishi, Ichiro Takeuchi

Comments: 47 pages, 3 figures, 16 tables

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[20] arXiv:2610.11459 [pdf, html, other]

Title: Feature Space Adaptation for Effortless Gaussian Process Flows

Thomas Cowperthwaite, Louis Sharrock, Lachlan Astfalck, Henry Moss

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Methodology (stat.ME)

[21] arXiv:2610.11407 [pdf, html, other]

Title: Beyond Distributional Fidelity: Causal-Penalized Diffusion for Synthetic Tabular Data

Lan Tao, Yongxian He, Shirong Xu, Yidong Ouyang, Guang Cheng

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[22] arXiv:2610.11139 [pdf, html, other]

Title: Accelerating Non-Smooth and Heavy-Tailed Sampling

Pervez Ali, Xiaoyu Wang, Yingli Wang, Lingjiong Zhu

Comments: 50 pages, 10 figures

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Probability (math.PR)

[23] arXiv:2610.11082 [pdf, html, other]

Title: A General $\widetildeΩ(\sqrt{T γ_T})$ Lower Bound for Kernel Bandits

Chenkai Ma, Jonathan Scarlett

Subjects: Machine Learning (stat.ML); Information Theory (cs.IT); Machine Learning (cs.LG)

[24] arXiv:2610.10870 [pdf, html, other]

Title: Transformed Samplers with Variance Reduction

Siran Liu, Michalis Tisias, Petros Dellaportas

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Methodology (stat.ME)

[25] arXiv:2610.10829 [pdf, html, other]

Title: Conformal Prediction under Partial Verification

Zijun Yu, Yu Gu, Vahid Partovi Nia, Masoud Asgharian

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[26] arXiv:2610.10793 [pdf, html, other]

Title: Calibrating Ambiguity Set via Diagnostic Transport for Distributionally Robust Optimization

Wenbin Zhou, Elizabeth Cucuzzella, Shixiang Zhu

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Optimization and Control (math.OC)

[27] arXiv:2610.10761 [pdf, html, other]

Title: What can linear attention learn from nonlinear teachers in-context?

Mary Letey, Arman Rysmakhanov, Yue M. Lu, Cengiz Pehlevan, Jacob Zavatone-Veth

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[28] arXiv:2610.10642 [pdf, html, other]

Title: From Log-Odds to Shapley Values: An Explanatory Geometry for the Weighted Naive Bayes Classifier

Vincent Lemaire, Fabrice Clérot

Comments: 15 pages

Subjects: Machine Learning (stat.ML); Artificial Intelligence (cs.AI); Machine Learning (cs.LG)

[29] arXiv:2610.10615 [pdf, html, other]

Title: JevForest: Path Voting for Budgeted Feature Acquisition

Yu Yan

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[30] arXiv:2610.10600 [pdf, html, other]

Title: The optimal information complexity of VC learning

Steve Hanneke, Juexiao Wang

Subjects: Machine Learning (stat.ML); Information Theory (cs.IT); Machine Learning (cs.LG); Statistics Theory (math.ST)

[31] arXiv:2610.12370 (cross-list from cs.LG) [pdf, html, other]

Title: Bilevel optimization for data-driven learning of Koopman embeddings using kernel-based autoencoders

Joel-Pascal Ntwali N'konzi, Feliks Nüske, Stefan Klus

Subjects: Machine Learning (cs.LG); Dynamical Systems (math.DS); Machine Learning (stat.ML)

[32] arXiv:2610.12362 (cross-list from cs.LG) [pdf, html, other]

Title: Closing the Horizon Gap in Policy Optimization for Adversarial MDPs

Mingyi Li, Taira Tsuchiya

Comments: 17 pages, 2 tables

Subjects: Machine Learning (cs.LG); Machine Learning (stat.ML)

[33] arXiv:2610.12328 (cross-list from cs.LG) [pdf, html, other]

Title: Composite Online-to-Nonconvex Conversion with Optimal Oracle Complexity

Mingyi Li, Taira Tsuchiya, Kenji Yamanishi

Comments: 27 pages, 3 figures, 2 tables

Subjects: Machine Learning (cs.LG); Optimization and Control (math.OC); Machine Learning (stat.ML)

[34] arXiv:2610.12211 (cross-list from cs.LG) [pdf, html, other]

Title: Verification with Transfer: Exact Information Frontiers and Their Price in Calls

Hazar Yueksel

Comments: 46 pages, of which 8 pages main text. The Lean 4 formalization is in the ancillary files

Subjects: Machine Learning (cs.LG); Cryptography and Security (cs.CR); Information Theory (cs.IT); Machine Learning (stat.ML)

[35] arXiv:2610.12115 (cross-list from cs.LG) [pdf, html, other]

Title: Credal Machine Learning for Risk-Averse Decision Making

Timo Löhr, Paul Hofman, Maximilian Muschalik, Eyke Hüllermeier

Subjects: Machine Learning (cs.LG); Machine Learning (stat.ML)

[36] arXiv:2610.12076 (cross-list from cs.LG) [pdf, html, other]

Title: Exploiting Gradients in Bayesian Inference of Expensive Simulators

Šimon Soldát, Václav Šmídl

Comments: 8 pages, 4 figures. Code: this https URL

Journal-ref: 2026 11th International Conference on Machine Learning Technologies (ICMLT), Berlin, Germany, 2026

Subjects: Machine Learning (cs.LG); Machine Learning (stat.ML)

[37] arXiv:2610.11772 (cross-list from math.ST) [pdf, html, other]

Title: Optimal random quantisers for spherically symmetric distributions

Luc Pronzato, Anatoly Zhigljavsky

Subjects: Statistics Theory (math.ST); Machine Learning (cs.LG); Machine Learning (stat.ML)

[38] arXiv:2610.11571 (cross-list from stat.AP) [pdf, html, other]

Title: Automated Detection of Match Phases in Football from Spatio-Temporal Tracking Data Using Graph Neural Networks

Vincent Renner, Nils Koster, Pascal Bauer, Melanie Schienle

Subjects: Applications (stat.AP); Machine Learning (stat.ML)

[39] arXiv:2610.11475 (cross-list from cs.LG) [pdf, html, other]

Title: Rare Gate Disagreements Can Limit Plasticity: When Gradient Flow Mispredicts Finite-Batch SGD

Ruoyu Zhao, Mingxuan Zhang, Jianbo Dai, Jiaqi Wu, Chenyu Zhu, Tong Che

Comments: 25 pages, 5 figures. Tong Che leads the project

Subjects: Machine Learning (cs.LG); Optimization and Control (math.OC); Machine Learning (stat.ML)

[40] arXiv:2610.11388 (cross-list from math.ST) [pdf, html, other]

Title: Sequential Conditional Independence Testing with Machine Learning Models

Angel Reyero-Lobo, Michele Meziu, Sebastian Uriel Arias, Peter Grünwald

Subjects: Statistics Theory (math.ST); Machine Learning (stat.ML)

[41] arXiv:2610.11309 (cross-list from cs.LG) [pdf, html, other]

Title: From Geometry to Generalization: Why Row Normalization Can Beat Adam and Muon

Jihwan Kim, Dogyoon Song, Chulhee Yun

Comments: 90 pages, 9 figures

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Optimization and Control (math.OC); Machine Learning (stat.ML)

[42] arXiv:2610.11266 (cross-list from stat.ME) [pdf, html, other]

Title: Regularized Small Area Estimation with Graph Laplacian Benchmarking priors

Jairo Fúquene-Patiño, Brenda Betancourt

Subjects: Methodology (stat.ME); Computation (stat.CO); Machine Learning (stat.ML)

[43] arXiv:2610.11226 (cross-list from cs.AI) [pdf, html, other]

Title: When Lower Reconstruction Loss Hurts: Distributionally Robust Refinement for Low-Bit LLM Quantization

Yanlong Zhao, Xiaoyuan Cheng, Huihang Liu, Baihua He, Xinyu Zhang, Harrison Bo Hua Zhu, Wenlong Chen, Li Zeng, Zhuo Sun

Subjects: Artificial Intelligence (cs.AI); Machine Learning (cs.LG); Machine Learning (stat.ML)

[44] arXiv:2610.11145 (cross-list from cs.DS) [pdf, html, other]

Title: Tight Bounds for Equivalence Testing with Non-Adaptive Conditional Samples

Gautam Kamath

Subjects: Data Structures and Algorithms (cs.DS); Information Theory (cs.IT); Machine Learning (stat.ML)

[45] arXiv:2610.11038 (cross-list from math.ST) [pdf, html, other]

Title: Decision-Sufficient Posterior Approximation

Sean Plummer

Comments: 45 pages, 1 figure

Subjects: Statistics Theory (math.ST); Machine Learning (stat.ML)

[46] arXiv:2610.10952 (cross-list from cs.LG) [pdf, html, other]

Title: SPD-MetaFormer is what you need for small-data brain decoding

Zhida Wang, Wei Lyu, Guo Yu, Sui Tang

Subjects: Machine Learning (cs.LG); Machine Learning (stat.ML)

[47] arXiv:2610.10666 (cross-list from cs.LG) [pdf, html, other]

Title: Explaining the Saliency Map Sparsity of Adversarially-Trained Neural Networks

Yannick Lunk, Atell Yehor Krasnopolsky, Damien Garreau, Leon Bungert

Subjects: Machine Learning (cs.LG); Optimization and Control (math.OC); Machine Learning (stat.ML)

[48] arXiv:2610.10640 (cross-list from math.ST) [pdf, html, other]

Title: How Many Directions Must a Truncated Diffusion Sampler Retain? Matching Bounds Under Power-Law Spectra

Radmehr Karimian, Ali Mohades, Johannes Lederer

Subjects: Statistics Theory (math.ST); Machine Learning (cs.LG); Machine Learning (stat.ML)

[49] arXiv:2610.10636 (cross-list from cs.LG) [pdf, html, other]

Title: D-SLR: The Disjoint Row-Sparse plus Low-Rank Decomposition

Vincent Szolnoky

Subjects: Machine Learning (cs.LG); Methodology (stat.ME); Machine Learning (stat.ML)

[50] arXiv:2610.10626 (cross-list from cs.LG) [pdf, html, other]

Title: Exact SO(3)-Equivariant Isotropic Kernels for Rotation-Robust Neural Dynamics

Ridham Patel

Comments: Accepted at NeurIPS 2026 Workshop NeurReps (Proceedings Track)

Subjects: Machine Learning (cs.LG); Computational Engineering, Finance, and Science (cs.CE); Machine Learning (stat.ML)