Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness

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Exponential Family Graphical Models: Correlated Replicates and Unmeasured Confounders, with Applications to fMRI Data

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Optimizing Return Distributions with Distributional Dynamic Programming

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Imprecise Multi-Armed Bandits: Representing Irreducible Uncertainty as a Zero-Sum Game

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Early Alignment in Two-Layer Networks Training is a Two-Edged Sword

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Generative Adversarial Networks: Dynamics

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"What is Different Between These Datasets?" A Framework for Explaining Data Distribution Shifts

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Assumption-lean and data-adaptive post-prediction inference

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Bagged Regularized k-Distances for Anomaly Detection

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Four Axiomatic Characterizations of the Integrated Gradients Attribution Method

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Fast Algorithm for Constrained Linear Inverse Problems

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High-Rank Irreducible Cartesian Tensor Decomposition and Bases of Equivariant Spaces

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Best Linear Unbiased Estimate from Privatized Contingency Tables

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Interpretable Global Minima of Deep ReLU Neural Networks on Sequentially Separable Data

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Enhanced Feature Learning via Regularisation: Integrating Neural Networks and Kernel Methods

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Data-Driven Performance Guarantees for Classical and Learned Optimizers

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Contextual Bandits with Stage-wise Constraints

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Boosting Causal Additive Models

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Frequentist Guarantees of Distributed (Non)-Bayesian Inference

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Asymptotic Inference for Multi-Stage Stationary Treatment Policy with Variable Selection

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