no code implementations • 6 Feb 2024 • Yuting Tang, Xin-Qiang Cai, Yao-Xiang Ding, Qiyu Wu, Guoqing Liu, Masashi Sugiyama
Instead, the learner only obtains rewards at the ends of bags, where a bag is defined as a partial sequence of a complete trajectory.
1 code implementation • 26 Oct 2023 • Yifei Peng, Yu Jin, Zhexu Luo, Yao-Xiang Ding, Wang-Zhou Dai, Zhong Ren, Kun Zhou
There are two levels of symbol grounding problems among the core challenges: the first is symbol assignment, i. e. mapping latent factors of neural visual generators to semantic-meaningful symbolic factors from the reasoning systems by learning from limited labeled data.
no code implementations • 17 Jun 2021 • Xin-Qiang Cai, Yao-Xiang Ding, Zi-Xuan Chen, Yuan Jiang, Masashi Sugiyama, Zhi-Hua Zhou
In many real-world imitation learning tasks, the demonstrator and the learner have to act under different observation spaces.
no code implementations • 9 Sep 2019 • Xin-Qiang Cai, Yao-Xiang Ding, Yuan Jiang, Zhi-Hua Zhou
One of the key issues for imitation learning lies in making policy learned from limited samples to generalize well in the whole state-action space.
no code implementations • NeurIPS 2018 • Yao-Xiang Ding, Zhi-Hua Zhou
In many real-world learning tasks, it is hard to directly optimize the true performance measures, meanwhile choosing the right surrogate objectives is also difficult.
no code implementations • 1 Sep 2016 • Yao-Xiang Ding, Zhi-Hua Zhou
One of the fundamental problems in crowdsourcing is the trade-off between the number of the workers needed for high-accuracy aggregation and the budget to pay.