Zobrazeno 1 - 10
of 174
pro vyhledávání: '"Cai, Haoyuan"'
Lower-bound analyses for nonconvex strongly-concave minimax optimization problems have shown that stochastic first-order algorithms require at least $\mathcal{O}(\varepsilon^{-4})$ oracle complexity to find an $\varepsilon$-stationary point. Some wor
Externí odkaz:
http://arxiv.org/abs/2406.13041
The optimistic gradient method is useful in addressing minimax optimization problems. Motivated by the observation that the conventional stochastic version suffers from the need for a large batch size on the order of $\mathcal{O}(\varepsilon^{-2})$ t
Externí odkaz:
http://arxiv.org/abs/2401.14585
We revisit the incremental autonomous exploration problem proposed by Lim & Auer (2012). In this setting, the agent aims to learn a set of near-optimal goal-conditioned policies to reach the $L$-controllable states: states that are incrementally reac
Externí odkaz:
http://arxiv.org/abs/2205.10729
Publikováno v:
In Solar Energy Materials and Solar Cells 1 October 2024 276
Autor:
Zhang, Lulu, Liu, Runye, Liu, Luyao, Xing, Xiaoxing, Cai, Haoyuan, Fu, Yongdong, Sun, Jianhai, Ruan, Wang, Chen, Jian, Qiu, Xianbo, Yu, Duli
Publikováno v:
In Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 5 June 2024 314
Quantum computers hold unprecedented potentials for machine learning applications. Here, we prove that physical quantum circuits are PAC (probably approximately correct) learnable on a quantum computer via empirical risk minimization: to learn a para
Externí odkaz:
http://arxiv.org/abs/2107.09078
Publikováno v:
In Applied Thermal Engineering 25 June 2023 228
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Publikováno v:
In Energy & Buildings 15 December 2022 277
Publikováno v:
In Journal of Quantitative Spectroscopy and Radiative Transfer September 2021 271