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  1. Mixtures of Gaussian Process Experts with SMC^2

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

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

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

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

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

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  7. 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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  8. Operator Learning for Hyperbolic PDEs

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  9. Optimal subsampling for high-dimensional partially linear models via machine learning methods

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

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

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  13. Linear Separation Capacity of Self-Supervised Representation Learning

    Published in JMLR (2026)
    Subjects: “…Artificial Intelligence & Machine Learning…”
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  14. 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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  15. Learning with Linear Function Approximations in Mean-Field Control

    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. Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness

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