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Accelerated and Stable Convergence with Anchored Generalized Optimistic Method
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Stochastic Linear Bandits with Parameter Noise
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High-Probability Convergence Guarantees of Decentralized SGD
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On Regret Bounds of Thompson Sampling for Bayesian Optimization
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Explaining Concept Shift with Interpretable Feature Attribution
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Dropout Universality: Scaling Laws and Optimal Scheduling at the Edge-of-Chaos
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Flow Matching Calibration for Simulation-Based Inference under Model Misspecification
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Contrastive Spectral Rectification: Test-Time Defense towards Zero-shot Adversarial Robustness of CLIP
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$\texttt{ShaplEIG}$: Bayesian Experimental Design for Shapley Value Estimation
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Adversarially Robust Control of Conditional Value-at-Risk via Rockafellar-Uryasev Conformal Inference
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Muon in Associative Memory Learning: Training Dynamics and Scaling Laws
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No Free Lunch: Non-Asymptotic Analysis of Prediction-Powered Inference
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Nonparametric Distribution Regression Re-calibration
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Beyond Softmax: A Natural Parameterization for Categorical Random Variables
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Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training
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NeuralFLoC: Neural Flow-Based Joint Registration and Clustering of Functional Data
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Differentially Private Range Subgraph Counting
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Repro - Theoretical Investigation on Inductive Bias of Isolation Forest
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Repro - Learning High-Dimensional Parity Functions with Product Networks using Gradient Descent
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Repro - Keep Everyone Happy: Online Fair Division of Numerous Items with Few Copies
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Repro - Full-Batch Gradient Descent Outperforms One-Pass SGD: Sample Complexity Separation in Single-Index Learning
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Repro - The Role of Target Update Frequencies in Q-Learning
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Repro - Black-Box Assisted Regression: Phase Transitions and Minimax Optimality
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Repro - Magnitude Distance: A Geometric Measure of Dataset Similarity
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