Search Results - Information Engineering

  1. A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs

    Subjects: “…Computer Science & Information Science…”
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  2. Error bounds for particle gradient descent, and extensions of the log-Sobolev and Talagrand inequalities

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  3. Linear Hypothesis Testing in High-Dimensional Expected Shortfall Regression with Heavy-Tailed Errors

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  4. Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling

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  5. Distribution Free Tests for Model Selection Based on Maximum Mean Discrepancy with Estimated Parameters

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  6. Statistical field theory for Markov decision processes under uncertainty

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  7. Bayesian Data Sketching for Varying Coefficient Regression Models

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  8. Bagged k-Distance for Mode-Based Clustering Using the Probability of Localized Level Sets

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  9. Linear cost and exponentially convergent approximation of Gaussian Matérn processes on intervals

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  10. Invariant Subspace Decomposition

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  11. Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights

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  12. Outlier Robust and Sparse Estimation of Linear Regression Coefficients

    Subjects: “…Computer Science & Information Science…”
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  13. Affine Rank Minimization via Asymptotic Log-Det Iteratively Reweighted Least Squares

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  14. Causal Effect of Functional Treatment

    Subjects: “…Computer Science & Information Science…”
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  15. Uplift Model Evaluation with Ordinal Dominance Graphs

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

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

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

    Subjects: “…Computer Science & Information Science…”
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  19. Integral Probability Metrics Meet Neural Networks: The Radon-Kolmogorov-Smirnov Test

    Subjects: “…Computer Science & Information Science…”
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  20. On Inference for the Support Vector Machine

    Subjects: “…Computer Science & Information Science…”
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