Journal Statistics

187
Journal of the Royal Statistical Society Series B
papers tracked
415
Journal of the American Statistical Association
papers tracked
163
Annals of Statistics
papers tracked
122
Biometrika
papers tracked
409
Journal of Machine Learning Research
papers tracked

Recent Papers

JMLR Jul 07, 2026
Bridging Domain Invariance and Diversity: A Fine-Grained Risk Bound for Domain Generalization

Xi Wang, Liang Bai, Xian Yang et al.

Machine Learning
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AOS Jul 07, 2026
SIMPLE-RC: Group Network Inference with Non-Sharp Nulls and Weak Signals

Jianqing Fan, Fan Yang, Yingying Fan et al.

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JMLR Jul 07, 2026
Global Fréchet Manifold Learning for Random Objects, With Application to Low-Dimensional Wasserstein Representations of Distributional Data

Hans-Georg Müller, Álvaro Gajardo

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JMLR Jul 07, 2026
Nonparametric generative modeling for time series via Schrödinger bridge

Mohamed Hamdouche, Pierre Henry-Labordère, Huyên Pham

Nonparametric Statistics High-Dimensional Statistics Time Series
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JASA Jul 07, 2026
Investigating Spatial Dynamics in Spatial Omics Data with StarTrail

Didong Li, Jiawen Chen, Caiwei Xiong et al.

Machine Learning
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Biometrika Jul 07, 2026
Post-reduction inference for confidence sets of models

H S Battey, D G Rasines, Y Tang

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Biometrika Jul 07, 2026
Integral Probability Metric-Guided CUSUM-Net for Nonparametric Changepoint Detection

Guanghui Wang, Yunchen Li, Zhou Yu et al.

Nonparametric Statistics
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JMLR Jul 06, 2026
High-Dimensional Analysis of Gradient Flow for Extensive-Width Quadratic Neural Networks

Francis Bach, Simon Martin, Giulio Biroli

Machine Learning High-Dimensional Statistics
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JMLR Jul 06, 2026
Error Analyses of Auto-Regressive Video Diffusion Models

Zhuoran Yang, Jing Wang, Fengzhuo Zhang et al.

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JMLR Jul 06, 2026
Near-optimal Delta-convex Estimation of Lipschitz Functions

G{\'{a}}bor Bal{\'{a}}zs

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JMLR Jul 06, 2026
The Sample Complexity of Parameter-Free Stochastic Convex Optimization

Jared Lawrence, Ari Kalinsky, Hannah Bradfield et al.

Computational Statistics
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JMLR Jul 06, 2026
End-to-End Deep Learning for Predicting Metric Space-Valued Outputs

Su I Iao, Yidong Zhou, Hans-Georg M{\"{u}}ller

Machine Learning
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JMLR Jul 06, 2026
Graph-based Clustering Revisited: A Relaxation of Kernel k-Means Perspective

Wenlong Lyu, Yuheng Jia, Hui Liu et al.

Nonparametric Statistics
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JMLR Jul 06, 2026
Learning to Play Two-Player Perfect-Information Games without Knowledge

Quentin Cohen-Solal

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JMLR Jul 06, 2026
Doubly Debiased Robust Subsampling for Transfer Learning

Tao Wang, Weng Kee Wong

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JMLR Jul 06, 2026
Abstract Gradient Training: A Unified Certification Framework for Data Poisoning, Unlearning, and Differential Privacy

Philip Sosnin, Matthew Wicker, Josh Collyer et al.

Machine Learning
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JMLR Jul 06, 2026
Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression

Giacomo Zanella, Filippo Ascolani

Machine Learning High-Dimensional Statistics
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JMLR Jul 06, 2026
Underdamped Langevin MCMC with third order convergence

Maximilian Scott, D{\'{a}}ire O'Kane, Andraž Jelinčič et al.

Bayesian Statistics
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JMLR Jul 06, 2026
Approximation-Free Differentiable Oblique Decision Trees

Subrat Prasad Panda, Blaise Genest, Arvind Easwaran

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JMLR Jul 06, 2026
Minimax Optimal Convergence of Gradient Descent in Logistic Regression via Large and Adaptive Stepsizes

Peter L. Bartlett, Ruiqi Zhang, Jingfeng Wu et al.

Machine Learning
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