Minimax Optimal Deep Neural Network Classifiers Under Smooth Decision Boundary

Subjects: “…Artificial Intelligence & Machine Learning…”
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Optimal and Efficient Algorithms for Decentralized Online Convex Optimization

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PREMAP: A Unifying PREiMage APproximation Framework for Neural Networks

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Score-Aware Policy-Gradient and Performance Guarantees using Local Lyapunov Stability

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On the O(sqrt(d)/T^(1/4)) Convergence Rate of RMSProp and Its Momentum Extension Measured by l_1 Norm

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Transformers from Diffusion: A Unified Framework for Neural Message Passing

Subjects: “…Artificial Intelligence & Machine Learning…”
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Modelling Populations of Interaction Networks via Distance Metrics

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BitNet: 1-bit Pre-training for Large Language Models

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Last-iterate Convergence of Shuffling Momentum Gradient Method under the Kurdyka-Lojasiewicz Inequality

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Posterior and Variational Inference for Deep Neural Networks with Heavy-Tailed Weights

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Maximum Causal Entropy IRL in Mean-Field Games and GNEP Framework for Forward RL

Subjects: “…Artificial Intelligence & Machine Learning…”
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Degree of Interference: A General Framework For Causal Inference Under Interference

Subjects: “…Artificial Intelligence & Machine Learning…”
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Quantifying the Effectiveness of Linear Preconditioning in Markov Chain Monte Carlo

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Sparse SVM with Hard-Margin Loss: a Newton-Augmented Lagrangian Method in Reduced Dimensions

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On Model Identification and Out-of-Sample Prediction of PCR with Applications to Synthetic Controls

Subjects: “…Artificial Intelligence & Machine Learning…”
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Bayesian Scalar-on-Image Regression with a Spatially Varying Single-layer Neural Network Prior

Subjects: “…Artificial Intelligence & Machine Learning…”
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DRM Revisited: A Complete Error Analysis

Subjects: “…Artificial Intelligence & Machine Learning…”
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Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers

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On the Statistical Properties of Generative Adversarial Models for Low Intrinsic Data Dimension

Subjects: “…Artificial Intelligence & Machine Learning…”
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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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