67 citations · 106 across the 3 of their papers we have counts for
3 papers
cs.LG2021★ 5 cited
Convergent and Efficient Deep Q Network Algorithm
Zhikang T. Wang, Masahito Ueda
Despite the empirical success of the deep Q network (DQN) reinforcement learning algorithm and its variants, DQN is still not well understood and it does not guarantee convergence.…
quant-ph2019★ 67 cited
Deep Reinforcement Learning Control of Quantum Cartpoles
Zhikang T. Wang, Yuto Ashida, Masahito Ueda
We generalize a standard benchmark of reinforcement learning, the classical cartpole balancing problem, to the quantum regime by stabilizing a particle in an unstable potential thr…
cs.LG2019★ 34 cited
Deep Gamblers: Learning to Abstain with Portfolio Theory
Liu Ziyin, Zhikang Wang, Paul Pu Liang +3
We deal with the \textit{selective classification} problem (supervised-learning problem with a rejection option), where we want to achieve the best performance at a certain level o…