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REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis
Yu-Shao Peng, Kai-Fu Tang, Hsuan-Tien Lin, Edward Chang
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Convergence-Rate-Matching Discretization of Accelerated Optimization Flows Through Opportunistic State-Triggered Control
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On the Power of Small-size Graph Neural Networks for Linear Programming
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Graph neural networks (GNNs) have recently emerged as powerful tools for addressing complex optimization problems.
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Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers
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We also provide an extensive theoretical analysis of our methods.
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