Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers

Subjects: “…Artificial Intelligence & Machine Learning…”
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Score-based Causal Representation Learning: Linear and General Transformations

Subjects: “…Artificial Intelligence & Machine Learning…”
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On the Statistical Properties of Generative Adversarial Models for Low Intrinsic Data Dimension

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Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms

Subjects: “…Artificial Intelligence & Machine Learning…”
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Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles

Subjects: “…Artificial Intelligence & Machine Learning…”
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Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed Learning Scheme for Data Silos

Subjects: “…Artificial Intelligence & Machine Learning…”
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On Global and Local Convergence of Iterative Linear Quadratic Optimization Algorithms for Discrete Time Nonlinear Control

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A Decentralized Proximal Gradient Tracking Algorithm for Composite Optimization on Riemannian Manifolds

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Learning conditional distributions on continuous spaces

Subjects: “…Artificial Intelligence & Machine Learning…”
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A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs

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Error bounds for particle gradient descent, and extensions of the log-Sobolev and Talagrand inequalities

Subjects: “…Artificial Intelligence & Machine Learning…”
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Linear Hypothesis Testing in High-Dimensional Expected Shortfall Regression with Heavy-Tailed Errors

Subjects: “…Artificial Intelligence & Machine Learning…”
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Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling

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

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Statistical field theory for Markov decision processes under uncertainty

Subjects: “…Artificial Intelligence & Machine Learning…”
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Bayesian Data Sketching for Varying Coefficient Regression Models

Subjects: “…Artificial Intelligence & Machine Learning…”
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Bagged k-Distance for Mode-Based Clustering Using the Probability of Localized Level Sets

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

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Invariant Subspace Decomposition

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

Subjects: “…Artificial Intelligence & Machine Learning…”
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