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  1. Extending Temperature Scaling with Homogenizing Maps

    Published in JMLR (2026)
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  2. Density Estimation Using the Perceptron

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  3. Simplex Constrained Sparse Optimization via Tail Screening

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  4. Score-Based Diffusion Models in Function Space

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  5. Regularized Rényi Divergence Minimization through Bregman Proximal Gradient Algorithms

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  6. WEFE: A Python Library for Measuring and Mitigating Bias in Word Embeddings

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  7. Frontiers to the learning of nonparametric hidden Markov models

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  8. On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes

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  9. Classification in the high dimensional Anisotropic mixture framework: A new take on Robust Interpolation

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  10. Universal Online Convex Optimization Meets Second-order Bounds

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  11. Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens

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  12. Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests

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  13. skglm: Improving scikit-learn for Regularized Generalized Linear Models

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  14. Losing Momentum in Continuous-time Stochastic Optimisation

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  15. Latent Process Models for Functional Network Data

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  16. Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models

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  17. On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory

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  18. Fine-grained Analysis and Faster Algorithms for Iteratively Solving Linear Systems

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  19. Deep Generative Models: Complexity, Dimensionality, and Approximation

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  20. ClimSim-Online: A Large Multi-Scale Dataset and Framework for Hybrid Physics-ML Climate Emulation

    Published in JMLR (2026)
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