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Applications of Closed-loop Control in Biomedical Interventions: From Neural Modulation to Diabetes Management
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Reinforcement Learning with Manifold Optimization
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Randomized Sketching for Data Fitting
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Conditional Sampling and Density Estimation with Triangular Convex Flows
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Reducing Operator Complexity in Algebraic Multigrid with Machine Learning Approaches
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Efficient Training of Input Convex Neural Networks Using Variable Projection
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Low-Rank Exploiting Optimization Methods for Inverse Problems and Machine Learning
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Pre-Training Graph Neural Networks for Data-Efficient Brain Network Analysis
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The Applications of Alternating Minimization Algorithms on Deep Learning Models
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Linear Programming Approach for Q-Learning
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