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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Sundeep Prabhakar Chepuri, Antonio G. Marques, Maulik Devmurari, Gonzalo Mateos: Signal Processing over Product DAGs: Causal Shifts and Filters arxiv.org/abs/2609.40275 arxiv.org/pdf/2609.40275 arxiv.org/html/2609.40275

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Yonghan Jung: Proximal Balancing for Causal Effect Estimation under Unmeasured Confounding arxiv.org/abs/2609.40051 arxiv.org/pdf/2609.40051 arxiv.org/html/2609.40051

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Daniel Habermann, Andreas Bulling, Stefan T. Radev, Paul-Christian B\"urkner: Amortized Bayesian Inference on Multilevel Models of Arbitrary Structure arxiv.org/abs/2609.40024 arxiv.org/pdf/2609.40024 arxiv.org/html/2609.40024

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Chenglin Li, Qiao Liu: BayesNDE: Bayesian Generative Modeling for Neural Density Estimation arxiv.org/abs/2609.39843 arxiv.org/pdf/2609.39843 arxiv.org/html/2609.39843

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Xabier de Juan, Santiago Mazuelas, Yilun Zhu, Clayton Scott: Estimation of the Label-Noise Transition Matrix with Performance Guarantees via Selective Classification arxiv.org/abs/2609.39829 arxiv.org/pdf/2609.39829 arxiv.org/html/2609.39829

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Olischl\"ager, Jedhoff, Kucharsk\'y, Mishra, Radev, B\"urkner: Mitigating Representation Gaps in Amortized Bayesian Inference with Auxiliary Supervision arxiv.org/abs/2609.39525 arxiv.org/pdf/2609.39525 arxiv.org/html/2609.39525

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Maxx Richard Rahman, Mostafa Hammouda, Wolfgang Maass: CAMOS: Coupled Oscillatory State-Space Model for Multimodal Clinical Time-Series arxiv.org/abs/2609.39484 arxiv.org/pdf/2609.39484 arxiv.org/html/2609.39484

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Elis Stefansson, David V\"avinggren, Ant\^onio H. Ribeiro: Distributionally robust linear regression through the lens of adversarial training arxiv.org/abs/2609.39449 arxiv.org/pdf/2609.39449 arxiv.org/html/2609.39449

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Juno Kim, Hengyu Fu, Peter Bartlett, Jason D. Lee, Jingfeng Wu: Principal Component Regression Dominates all Monotone Spectral Filters for Linear Regression arxiv.org/abs/2609.39440 arxiv.org/pdf/2609.39440 arxiv.org/html/2609.39440

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Yuxuan Han, Xiaoyu Fan, Jiawei Zhang, Zhengyuan Zhou: Towards Optimal Inventory Control under Censored Demand: A Biased Sample-Average Approximation Approach arxiv.org/abs/2609.39397 arxiv.org/pdf/2609.39397 arxiv.org/html/2609.39397

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Th\'eo Marchetta, Filippo Alessandroni, Alessandro Breccia, Alessandro Ingrosso, Federica Gerace: A Dynamical Theory of LoRA in Continual Learning arxiv.org/abs/2609.39367 arxiv.org/pdf/2609.39367 arxiv.org/html/2609.39367

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Euijong Song, Hyewon Park, Gunwoong Park: Discrete Score Matching Enables Causal Discovery from Count Data arxiv.org/abs/2609.39326 arxiv.org/pdf/2609.39326 arxiv.org/html/2609.39326

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Baptiste Ferrere, Fabrice Gamboa, Jean-Michel Loubes: Minimax Additive Regression under Unknown Dependent Designs arxiv.org/abs/2609.39212 arxiv.org/pdf/2609.39212 arxiv.org/html/2609.39212

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Yugo Nakayama: Asymptotic Properties of Support Vector Machines in High-Dimension, Low-Sample-Size Settings under a Spiked Model arxiv.org/abs/2609.39173 arxiv.org/pdf/2609.39173 arxiv.org/html/2609.39173

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Takakura, Wachi, Higuchi, Miyaguchi, Suzuki: Steepest Guidance: A Practical and Principled Approach to Inference-Time Alignment of Flow and Diffusion-based Models arxiv.org/abs/2609.39091 arxiv.org/pdf/2609.39091 arxiv.org/html/2609.39091

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Songqiu Ma, Yunfei Yang: Minimax rates for learning spectral Barron functions by deep ReLU neural networks arxiv.org/abs/2609.39020 arxiv.org/pdf/2609.39020 arxiv.org/html/2609.39020

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Wilson G. Gregory, George A. Kevrekidis, Ben Blum-Smith, Soledad Villar: Warm-starting PDE solvers with any-dimensional machine learning arxiv.org/abs/2609.38916 arxiv.org/pdf/2609.38916 arxiv.org/html/2609.38916

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Yang Peng: Sharp Statistical Rates for Asynchronous TD Learning with Markovian Data arxiv.org/abs/2609.38880 arxiv.org/pdf/2609.38880 arxiv.org/html/2609.38880

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Kaixuan Ji, Qiwei Di, Qingyue Zhao, Heyang Zhao, Quanquan Gu: Bandits with Multiple Optimal Arms: Minimax Regret and Non-Adaptivit arxiv.org/abs/2609.38659 arxiv.org/pdf/2609.38659 arxiv.org/html/2609.38659

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Michael Wieck-Sosa, Cosma Rohilla Shalizi: Generative sequence modeling for infinite memory processes via predictive states arxiv.org/abs/2609.38524 arxiv.org/pdf/2609.38524 arxiv.org/html/2609.38524

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Ouyang, Wan, Haris, Tan, Peng, Li, Lin, Chen, Karimzadehgan, Go, Michailidis: Acceleration of Diffusion Language Model through Discrete Average Generator arxiv.org/abs/2609.38364 arxiv.org/pdf/2609.38364 arxiv.org/html/2609.38364

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

Daniela De Canditiis, Italia De Feis, Paola Stolfi: Robust LassoNet: Enhancing Feature Selection in Neural Networks via Robust Loss Functions arxiv.org/abs/2609.38263 arxiv.org/pdf/2609.38263 arxiv.org/html/2609.38263

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 3h

[2026-10-01 Thu (UTC), 23 new articles found for statML Machine Learning]

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Bruno Marcondes e Resende, Helton Graziadei, Thiago Rodrigo Ramos, Rafael Izbicki: ReCIRC: Rectified Conformal Risk Control arxiv.org/abs/2609.38112 arxiv.org/pdf/2609.38112 arxiv.org/html/2609.38112

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Chlo\'e Hashimoto-Cullen, Amaury Durand, Laurent Bozzi, Benjamin Guedj, Yannig Goude, Sylvain Le Corff: Latent Inference-Time Guidance of Time Series Foundation Models arxiv.org/abs/2609.38058 arxiv.org/pdf/2609.38058 arxiv.org/html/2609.38058

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Julien Boussard, Antoine D\'{e}bouchage, Th\'{e}o Saulus: Identifiability Guarantees for Drivers and Dynamics of Delayed Physical Systems arxiv.org/abs/2609.37944 arxiv.org/pdf/2609.37944 arxiv.org/html/2609.37944

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Cao Le Cong Thanh, Dang Quang Vinh, Vo Nguyen Le Duy: Post-Anomaly Detection Inference for Deep SVDD arxiv.org/abs/2609.37935 arxiv.org/pdf/2609.37935 arxiv.org/html/2609.37935

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Gwendal Debaussart-Joniec (CB, ENS Paris Saclay), Th\'eau Blanchard (HeKA | U1346, GE Healthcare), Argyris Kalogeratos (CB, ENS Paris Saclay): A Finslerian Approach for Embedding Directed Data arxiv.org/abs/2609.37649 arxiv.org/pdf/2609.37649 arxiv.org/html/2609.37649

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Attila Lovas, L\'or\'ant Nagy: Ornstein-Uhlenbeck Is Hard to Beat, Yet Superlinear Drift Ships Lower Transport Costs arxiv.org/abs/2609.37579 arxiv.org/pdf/2609.37579 arxiv.org/html/2609.37579

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Futoshi Futami, Jerry Huang, Ichiro Takeuchi: Hierarchical Utility Calibration for Structured Multiclass Decisions arxiv.org/abs/2609.36532 arxiv.org/pdf/2609.36532 arxiv.org/html/2609.36532

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Yinan Cheng, Lili Zheng: LOCO-AdaMP: Built-in LOCO Inference for Adaptive Minipatch Ensembles with Enhanced Prediction arxiv.org/abs/2609.36396 arxiv.org/pdf/2609.36396 arxiv.org/html/2609.36396

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Shitong Wang, Zhongang Cai, Yuzhou Hong: One-Step Next-Latent Prediction Is Not a World Model arxiv.org/abs/2609.36227 arxiv.org/pdf/2609.36227 arxiv.org/html/2609.36227

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

[2026-09-30 Wed (UTC), 10 new articles found for statML Machine Learning]

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Sakshi Arya, Cheng Soon Ong: Elicitation and Decision Geometry in Single-Index Bandits arxiv.org/abs/2609.35622 arxiv.org/pdf/2609.35622 arxiv.org/html/2609.35622

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Thiago Ramos, Alek Fr\"ohlich, Daniel Perazzo, Massimiliano Pontil: Learning Conditional Expectation Operators via Functional Newton Updates arxiv.org/abs/2609.35598 arxiv.org/pdf/2609.35598 arxiv.org/html/2609.35598

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Chemlal, Germain, Flamary, Kostic, Lounici: Multi-Task Learning of Conditional Mean Operators: applications to dynamical systems and uncertainty quantification arxiv.org/abs/2609.35429 arxiv.org/pdf/2609.35429 arxiv.org/html/2609.35429

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Niklas Koenen, Claudia Battistin, Jeriek Van den Abeele, Martin Jullum: A Hierarchy of Entropy-Shapley Games for Multivariate Predictive Uncertainty arxiv.org/abs/2609.35217 arxiv.org/pdf/2609.35217 arxiv.org/html/2609.35217

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Jintao Wei, Chenxi Li, Songhao Wang: GUIDE-FBO: Guidance via Uncertainty Intervention and Distributional Exchange for Federated Bayesian Optimization arxiv.org/abs/2609.35038 arxiv.org/pdf/2609.35038 arxiv.org/html/2609.35038

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Sungwoo Park, Sunghee Park, Won Chang: Conformal Prediction and Conditional Coverage for Tabular Foundation Models arxiv.org/abs/2609.34887 arxiv.org/pdf/2609.34887 arxiv.org/html/2609.34887

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Alexandre Decl\`eves, Etienne Boursier, Nicolas Flammarion: Statistical Benefits of Fine-Tuning from Pretrained Initialization in Diagonal Linear Networks arxiv.org/abs/2609.34756 arxiv.org/pdf/2609.34756 arxiv.org/html/2609.34756

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Masoud Kavian, Abdellatif Zaidi, Milad Sefidgaran: Information-Theoretic Analysis of Next-Token Prediction under Markovian Data arxiv.org/abs/2609.34731 arxiv.org/pdf/2609.34731 arxiv.org/html/2609.34731

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Etienne Boursier, Nicolas Flammarion: Two-Timescale Fine-tuning Provably Learns New Features for Two-Layer ReLU Networks arxiv.org/abs/2609.34667 arxiv.org/pdf/2609.34667 arxiv.org/html/2609.34667

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Zeyuan Yu, Zhi Chang, Shiwei Lan: Probabilistic Geodesic Flow Matching on Location-Scale Families arxiv.org/abs/2609.34613 arxiv.org/pdf/2609.34613 arxiv.org/html/2609.34613

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Aram Ebtekar, Marcus Hutter, Danica J. Sutherland: Understanding Generalization Requires Universal Induction arxiv.org/abs/2609.34458 arxiv.org/pdf/2609.34458 arxiv.org/html/2609.34458

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Peida Wu, Xinyang Xiong, Pengcheng Zeng: Functional Autoencoders for Amplitude-Phase Representation Learning arxiv.org/abs/2609.34207 arxiv.org/pdf/2609.34207 arxiv.org/html/2609.34207

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Yingbo Zhao, Zeyu Yang, Zhoufan Zhu: AlphaPareto: Formulaic Alpha Discovery with LLM-Guided Multi-Objective Reinforcement Learning arxiv.org/abs/2609.34188 arxiv.org/pdf/2609.34188 arxiv.org/html/2609.34188

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Wonmo Koo, Jaeyeong Lee, Taeseong Yoon, Heeyoung Kim: GT-PSSM: Unified Probabilistic Framework for Stochastic Dynamics Modeling and Dependency Learning in Multivariate Time Series Anomaly Det... arxiv.org/abs/2609.34161 arxiv.org/pdf/2609.34161 arxiv.org/html/2609.34161

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 29/09/2026

Sunmin Oh, Seungsu Han, Gunwoong Park: The Statistical Cost of Causal Discovery with Feedback arxiv.org/abs/2609.34050 arxiv.org/pdf/2609.34050 arxiv.org/html/2609.34050

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