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  1. Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  2. Sparse Semiparametric Discriminant Analysis for High-dimensional Zero-inflated Data

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  3. Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  4. Decentralized Asynchronous Optimization with DADAO allows Decoupling and Acceleration

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  5. Mixtures of Gaussian Process Experts with SMC^2

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  6. Robust Point Matching with Distance Profiles

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  7. BoFire: Bayesian Optimization Framework Intended for Real Experiments

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  8. Reliever: Relieving the Burden of Costly Model Fits for Changepoint Detection

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  9. Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  10. Are Ensembles Getting Better All the Time?

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  11. An Adaptive Parameter-free and Projection-free Restarting Level Set Method for Constrained Convex Optimization Under the Error Bound Condition

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  12. Decentralized Sparse Linear Regression via Gradient-Tracking

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  13. Calibrated Inference: Statistical Inference that Accounts for Both Sampling Uncertainty and Distributional Uncertainty

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  14. Relaxed Gaussian Process Interpolation: a Goal-Oriented Approach to Bayesian Optimization

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  15. On the Convergence of Projected Policy Gradient for Any Constant Step Sizes

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  16. A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  17. Model-free Change-Point Detection Using AUC of a Classifier

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  18. EF21 with Bells & Whistles: Six Algorithmic Extensions of Modern Error Feedback

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  19. Multiple Instance Verification

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  20. Exponential Family Graphical Models: Correlated Replicates and Unmeasured Confounders, with Applications to fMRI Data

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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