39 citations · 65 across the 9 of their papers we have counts for
10 papers
Active Representation Learning for General Task Space with Applications in Robotics
Yifang Chen, Yingbing Huang, Simon S. Du +2
Representation learning based on multi-task pretraining has become a powerful approach in many domains. In particular, task-aware representation learning aims to learn an optimal r…
Improved Adaptive Algorithm for Scalable Active Learning with Weak Labeler
Yifang Chen, Karthik Sankararaman, Alessandro Lazaric +6
Active learning with strong and weak labelers considers a practical setting where we have access to both costly but accurate strong labelers and inaccurate but cheap predictions pr…
Active Multi-Task Representation Learning
Yifang Chen, Simon S. Du, Kevin Jamieson
To leverage the power of big data from source tasks and overcome the scarcity of the target task samples, representation learning based on multi-task pretraining has become a stand…
Corruption Robust Active Learning
Yifang Chen, Simon S. Du, Kevin Jamieson
We conduct theoretical studies on streaming-based active learning for binary classification under unknown adversarial label corruptions. In this setting, every time before the lear…
Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
Yifang Chen, Simon S. Du, Kevin Jamieson
We study episodic reinforcement learning under unknown adversarial corruptions in both the rewards and the transition probabilities of the underlying system. We propose new algorit…
More Practical and Adaptive Algorithms for Online Quantum State Learning
Yifang Chen, Xin Wang
Online quantum state learning is a recently proposed problem by Aaronson et al. (2018), where the learner sequentially predicts -qubit quantum states based on given measurements…