Exact Theory and Optimal Stepsizes for Stochastic Gradient Descent in Smooth Convex Minimization
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A Neural Network Approach towards Real-Time Knot Point Density Estimates for the Nonlinear Quadrotor
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Hard Constraint Projection in a Physics Informed Neural Network (Burgers)
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Empirical Evaluation of Quantum Kernel Methods for Classification: A Comparative Study with Classical Kernels
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When Is a Game a Markov Decision Process? Correspondences Between Game Theory and Reinforcement Learning
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WASABI: Wasserstein Sampling via Bridge Interpolants
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Shock Loading Accesses Reaction Pathways beyond Accelerated Thermolysis
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Variance Reduction for Decentralized Stochastic Optimization with Multiple Local Updates
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Statistical Foundations of Reinforcement Learning: A Non-Asymptotic Perspective
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On-Chain Behavioral Signatures for Classifying Centralized Exchange Addresses on Ethereum Using Proof-of-Reserves
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Learning Nonlocal Interactions in Large-Scale Heterogeneous Metamaterials through Scientific Machine Learning
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Overcoming the Representational Limitations of Amplitude Encoding for Quantum Neural Networks
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