5 citations · 15 across the 5 of their papers we have counts for
5 papers
Model Spider: Learning to Rank Pre-Trained Models Efficiently
Yi-Kai Zhang, Ting-Ji Huang, Yao-Xiang Ding +2
Figuring out which Pre-Trained Model (PTM) from a model zoo fits the target task is essential to take advantage of plentiful model resources. With the availability of numerous hete…
A Coalition Formation Game Approach for Personalized Federated Learning
Leijie Wu, Song Guo, Yaohong Ding +2
Facing the challenge of statistical diversity in client local data distribution, personalized federated learning (PFL) has become a growing research hotspot. Although the state-of-…
Seeing Differently, Acting Similarly: Heterogeneously Observable Imitation Learning
Xin-Qiang Cai, Yao-Xiang Ding, Zi-Xuan Chen +3
In many real-world imitation learning tasks, the demonstrator and the learner have to act under different observation spaces. This situation brings significant obstacles to existin…
Imitation Learning from Pixel-Level Demonstrations by HashReward
Xin-Qiang Cai, Yao-Xiang Ding, Yuan Jiang +1
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. This problem is much more severe…
Crowdsourcing with Unsure Option
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. For saving budget, i…