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Improving Sampling and Function Approximation in Machine Learning Methods for Solving Partial Differential Equations
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Reinforcement Learning with Manifold Optimization
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Parameter Tuning for SIR-Related Models With Variational and Bayesian Methods
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Low Precision Preconditioning for Iterated Tikhonov Regularization
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Reducing Operator Complexity in Algebraic Multigrid with Machine Learning Approaches
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Linear Programming Approach for Q-Learning
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Variance Reduction Methods for High-Dimensional Optimal Control Problems
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Nonnegative Matrix Factorization for Music - Tuning the NMF Algorithm with Regularization
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Image Deblurring using Radial Basis functions for Interpolating Weights of Spatially Variant Blur
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Fair Clustering Problems
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