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    Graph-based Clustering Revisited: A Relaxation of Kernel k-Means Perspective

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    Learning to Play Two-Player Perfect-Information Games without Knowledge

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    Doubly Debiased Robust Subsampling for Transfer Learning

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

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    Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression

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    Underdamped Langevin MCMC with third order convergence

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    Approximation-Free Differentiable Oblique Decision Trees

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    Minimax Optimal Convergence of Gradient Descent in Logistic Regression via Large and Adaptive Stepsizes

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    Adaptive Nonparametric Perturbations of Parametric Models with Generalized Bayes

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    Robust training of implicit generative models for multivariate and heavy-tailed distributions with an invariant statistical loss

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    Gradient Span Algorithms Make Predictable Progress in High Dimension

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    py/cuTAGI: An Open-Source Library for Tractable Approximate Gaussian Inference in Bayesian Neural Networks

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    Statistical Test for Attention in Transformers for Images and Time Series

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    Accelerating Constrained Sampling: A Large Deviations Approach

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    Learning general conditional independence structures via the neighbourhood lattice

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    Statistical guarantees for denoising reflected diffusion models

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    Vecchia-Inducing-Points Full-Scale Approximations for Gaussian Processes

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    STDE++: Polynomial-Time Amortization for Linear Differential Operators

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    The Within-Orbit Adaptive Leapfrog No-U-Turn Sampler

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    MooBench: A micro-benchmark for performance overhead measurement of observability tools

    Published in Journal of Open Source Software (2026)
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