1 code implementation • 4 Jun 2023 • Wei-Fang Sun, Cheng-Kuang Lee, Simon See, Chun-Yi Lee
In fully cooperative multi-agent reinforcement learning (MARL) settings, environments are highly stochastic due to the partial observability of each agent and the continuously changing policies of other agents.
Ranked #1 on SMAC on SMAC 26m_vs_30m
no code implementations • 17 Dec 2022 • Tsung-Ming Tai, Giuseppe Fiameni, Cheng-Kuang Lee, Simon See, Oswald Lanz
Consequently, existing solutions based on the action recognition models are only suboptimal.
no code implementations • 22 Jun 2022 • Tsung-Ming Tai, Oswald Lanz, Giuseppe Fiameni, Yi-Kwan Wong, Sze-Sen Poon, Cheng-Kuang Lee, Ka-Chun Cheung, Simon See
In this report, we describe the technical details of our submission for the EPIC-Kitchen-100 action anticipation challenge.
1 code implementation • 2 Jun 2022 • Tsung-Ming Tai, Giuseppe Fiameni, Cheng-Kuang Lee, Simon See, Oswald Lanz
To this end, we propose a unified recurrence modeling for video action anticipation via message passing framework.
no code implementations • 18 Oct 2021 • Yi-Chen Chen, Shu-wen Yang, Cheng-Kuang Lee, Simon See, Hung-Yi Lee
It has been shown that an SSL pretraining model can achieve excellent performance in various downstream tasks of speech processing.
1 code implementation • 7 May 2021 • Yi-Chen Chen, Po-Han Chi, Shu-wen Yang, Kai-Wei Chang, Jheng-Hao Lin, Sung-Feng Huang, Da-Rong Liu, Chi-Liang Liu, Cheng-Kuang Lee, Hung-Yi Lee
The multi-task learning of a wide variety of speech processing tasks with a universal model has not been studied.
1 code implementation • 17 Apr 2021 • Tsung-Ming Tai, Giuseppe Fiameni, Cheng-Kuang Lee, Oswald Lanz
Endowing visual agents with predictive capability is a key step towards video intelligence at scale.
1 code implementation • 16 Feb 2021 • Wei-Fang Sun, Cheng-Kuang Lee, Chun-Yi Lee
In fully cooperative multi-agent reinforcement learning (MARL) settings, the environments are highly stochastic due to the partial observability of each agent and the continuously changing policies of the other agents.
Ranked #1 on SMAC on SMAC 27m_vs_30m
no code implementations • 13 May 2020 • Yi-Chen Chen, Jui-Yang Hsu, Cheng-Kuang Lee, Hung-Yi Lee
In order to examine the generalizability of DARTS-ASR, we apply our approach not only on many languages to perform monolingual ASR, but also on a multilingual ASR setting.