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cs.LG2026
Deep Q-Learning on Hölder Spaces
Qian Qi
We study the operator-theoretic core of Q-learning in continuous-time stochastic control with continuous states and actions. In value-based reinforcement learning, each Q-learning…
cs.LG2025
Neural Hamiltonian Operator
Qian Qi
Stochastic control problems in high dimensions are notoriously difficult to solve due to the curse of dimensionality. An alternative to traditional dynamic programming is Pontryagi…
cs.LG2025
Optimal Depth of Neural Networks
Qian Qi
Determining the optimal depth of a neural network is a fundamental yet challenging problem, typically resolved through resource-intensive experimentation. This paper introduces a f…