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  1. Affine Rank Minimization via Asymptotic Log-Det Iteratively Reweighted Least Squares

    Published in JMLR (2026)
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  2. Causal Effect of Functional Treatment

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  3. Uplift Model Evaluation with Ordinal Dominance Graphs

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  4. High-Dimensional L2-Boosting: Rate of Convergence

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  5. Feature Learning in Finite-Width Bayesian Deep Linear Networks with Multiple Outputs and Convolutional Layers

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  6. How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences

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  7. Integral Probability Metrics Meet Neural Networks: The Radon-Kolmogorov-Smirnov Test

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  8. On Inference for the Support Vector Machine

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  9. Random Pruning Over-parameterized Neural Networks Can Improve Generalization: A Training Dynamics Analysis

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  10. Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability

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  11. Implicit vs Unfolded Graph Neural Networks

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  12. Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification

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  13. GraphNeuralNetworks.jl: Deep Learning on Graphs with Julia

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  14. Dynamic angular synchronization under smoothness constraints

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  15. Derivative-Informed Neural Operator Acceleration of Geometric MCMC for Infinite-Dimensional Bayesian Inverse Problems

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  16. Wasserstein F-tests for Frechet regression on Bures-Wasserstein manifolds

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  17. Distributed Stochastic Bilevel Optimization: Improved Complexity and Heterogeneity Analysis

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  18. Learning causal graphs via nonlinear sufficient dimension reduction

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  19. On Consistent Bayesian Inference from Synthetic Data

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  20. Optimization Over a Probability Simplex

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