Ryan Wiley PRO

rdubwiley

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rdubwiley/transformers-efficiently-perform-in-context-logistic-regression-via-normalized-repro

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rdubwiley/domain-shift-aware-conformal-prediction-for-large-language-models-repro

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rdubwiley/learning-high-dimensional-parity-functions-with-product-networks-using-gradient-repro

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Repro - Transformers Efficiently Perform In-Context Logistic Regression via Normalized Gradient Descent

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Repro - A Task-centric Theory for Iterative Self-Improvement with Easy-to-Hard Curricula

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Repro - Dataset Distillation Efficiently Encodes Low-Dimensional Representations from Gradient-Based Learning of Non-Linear Tasks

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Repro - Domain-Shift-Aware Conformal Prediction for Large Language Models

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Repro - Learning High-Dimensional Parity Functions with Product Networks using Gradient Descent

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Repro - Universal Learning of Nonlinear Dynamics

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Repro - Tight Stability Bounds for Robust Distributed Learning: Byzantine Failures Hurt Generalization More than Data Poisoning

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Repro - On the Power of Source Screening for Learning Shared Feature Extractors

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Repro - Flow Matching Calibration for Simulation-Based Inference under Model Misspecification

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Repro - Bridging the Gap Between Average and Discounted TD Learning

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Repro - Hedging on the Frontier: Learning New Tasks with Few Samples

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Repro - On the Coordination of Value-Maximizing Bidders

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Repro - Stability beyond Bounded Differences: Sharp Generalization Bounds under Finite $L_p$ Moments

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Repro - Positive Distribution Shift as a Framework for Understanding Tractable Learning

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Repro - On the Accuracy of Newton Step and Influence Function Data Attributions

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Repro - Black-Box Assisted Regression: Phase Transitions and Minimax Optimality

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Repro - Sharp Empirical Bernstein Inequalities for the Variance of Bounded Random Variables

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Repro - Fine-Tuning Without Forgetting In-Context Learning: A Theoretical Analysis of Linear Attention Models

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Repro - Theoretical Investigation on Inductive Bias of Isolation Forest

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Repro - Understanding Generalization and Forgetting in In-Context Continual Learning

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