Zobrazeno 1 - 10
of 6 098
pro vyhledávání: '"Yi, Shan"'
Off-policy actor-critic algorithms have shown promise in deep reinforcement learning for continuous control tasks. Their success largely stems from leveraging pessimistic state-action value function updates, which effectively address function approxi
Externí odkaz:
http://arxiv.org/abs/2406.03890
PAC-Bayesian analysis is a frequentist framework for incorporating prior knowledge into learning. It was inspired by Bayesian learning, which allows sequential data processing and naturally turns posteriors from one processing step into priors for th
Externí odkaz:
http://arxiv.org/abs/2405.14681
Autor:
Hsieh, Chung-Han, Wong, Yi-Shan
This paper studies a risk-sensitive decision-making problem under uncertainty. It considers a decision-making process that unfolds over a fixed number of stages, in which a decision-maker chooses among multiple alternatives, some of which are determi
Externí odkaz:
http://arxiv.org/abs/2404.13371
Protein classification tasks are essential in drug discovery. Real-world protein structures are dynamic, which will determine the properties of proteins. However, the existing machine learning methods, like ProNet (Wang et al., 2022a), only access li
Externí odkaz:
http://arxiv.org/abs/2403.14736
Autor:
Jin, Yueqiao, Echeverria, Vanessa, Yan, Lixiang, Zhao, Linxuan, Alfredo, Riordan, Tsai, Yi-Shan, Gašević, Dragan, Martinez-Maldonado, Roberto
Multimodal Learning Analytics (MMLA) integrates novel sensing technologies and artificial intelligence algorithms, providing opportunities to enhance student reflection during complex, collaborative learning experiences. Although recent advancements
Externí odkaz:
http://arxiv.org/abs/2402.19071
Reinforcement learning for continuous control under sparse rewards is an under-explored problem despite its significance in real life. Many complex skills build on intermediate ones as prerequisites. For instance, a humanoid locomotor has to learn ho
Externí odkaz:
http://arxiv.org/abs/2402.03055
The cold posterior effect (CPE) (Wenzel et al., 2020) in Bayesian deep learning shows that, for posteriors with a temperature $T<1$, the resulting posterior predictive could have better performances than the Bayesian posterior ($T=1$). As the Bayesia
Externí odkaz:
http://arxiv.org/abs/2310.01189
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Studying the effects of weathering on the mechanical properties and microscopic evolution of weathered granite soil (WGS) is essential for connecting microstructure with macroscopic behavior. This study conducts systematic monotonic and cycl
Externí odkaz:
https://doaj.org/article/6fc3ad4ef1e94cd4b199c6fa31f36323
We propose a content-based system for matching video and background music. The system aims to address the challenges in music recommendation for new users or new music give short-form videos. To this end, we propose a cross-modal framework VMCML that
Externí odkaz:
http://arxiv.org/abs/2303.12379
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-8 (2024)
Abstract Microwave impedance microscopy (MIM) is an emerging scanning probe technique for nanoscale complex permittivity mapping and has made significant impacts in diverse fields. To date, the most significant hurdles that limit its widespread use a
Externí odkaz:
https://doaj.org/article/bed47f6eb8384d909ab5d570c78ea214