Stat.ML Papers

Unofficial updates of statistical machine learning papers on arXiv

[Stat.ML Papers @StatMLPapers]

Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis https://t.co/ihToX9BHXE

[Stat.ML Papers @StatMLPapers]

CausalGrade: Evidence-Guided Causal Graph Scoring with Jev https://t.co/UC4wBT3X5U

[Stat.ML Papers @StatMLPapers]

The Geometry of Multitask Learning: Sharp Rates for Shared Subspace Estimation https://t.co/RZBGDJPJqR

[Stat.ML Papers @StatMLPapers]

INLA for Adaptive UAV Sampling of Radio Environment Maps in IoT Networks: Prior Width Governs Accuracy and Calibration https://t.co/NHqQ2lhaFp

[Stat.ML Papers @StatMLPapers]

Robust-by-Design Distributional Learning from Contaminated Samples https://t.co/m74DJzvYI2

[Stat.ML Papers @StatMLPapers]

Adaptive Uncertainty Quantification on Simplicial Complexes with Conformalized Simplicial Neural Networks https://t.co/v1SucngPvU

[Stat.ML Papers @StatMLPapers]

Coarse-Graining Optimal Transport for Rollout-Free Post-Training of Flow Matching https://t.co/8wQlwNzLKK

[Stat.ML Papers @StatMLPapers]

Conditional Neural SDEs for Financial Time-Series Generation https://t.co/FkaV1wNPVU

[Stat.ML Papers @StatMLPapers]

Reliability-Weighted Direct Preference Optimization: Penalized Weights for Robust Preference Learning https://t.co/2XFToUn1IU

[Stat.ML Papers @StatMLPapers]

PDE-Residual-Informed Kriging https://t.co/gBgfH1yLE4

[Stat.ML Papers @StatMLPapers]

Statistical Foundations of Reinforcement Learning: A Non-Asymptotic Perspective https://t.co/FSetKmNFnP

[Stat.ML Papers @StatMLPapers]

WASABI: Wasserstein Sampling via Bridge Interpolants https://t.co/ZGC1gGz73M

[Stat.ML Papers @StatMLPapers]

Regret-Optimal Wasserstein-Robust Linear Regression https://t.co/kUNDAyUx3F

[Stat.ML Papers @StatMLPapers]

Dual-Corrected Stochastic Block Model ($\text{DC}^2\text{SBM}$): A Generalized Structure Detection Method for Attributed Networks https://t.co/lCyTX4bH8D

[Stat.ML Papers @StatMLPapers]

Certified Behavioral Retention for Continual Adaptation with Held-Out Anchors https://t.co/haoUy4cBDF

[Stat.ML Papers @StatMLPapers]

Near-Optimal First-Order Regret for Bandits with Feedback Graphs https://t.co/2ujdzs9oo2

[Stat.ML Papers @StatMLPapers]

Density-Guided Bootstrap Boundaries for Latent World-Model Reinforcement Learning https://t.co/NnlmDlpJtN

[Stat.ML Papers @StatMLPapers]

Omniprediction for All Mixable Proper Losses and Beyond https://t.co/9Hf254c65F

[Stat.ML Papers @StatMLPapers]

Where, When, and How Many Bits? Scaling Laws for SGD with Stochastic Rounding https://t.co/t0AS4AaI3V

[Stat.ML Papers @StatMLPapers]

MUON-RT Reusing the Teacher's Trajectory for Momentum-Free Muon for LLM Self-Distillation https://t.co/CE0BjrfJs2