Deep Safe Multi-Task Learning

no code implementations • 20 Nov 2021 • Zhixiong Yue, Feiyang Ye, Yu Zhang, Christy Liang, Ivor W. Tsang

We theoretically study the safeness of both learning strategies in the DSMTL model to show that the proposed methods can achieve some versions of safe multi-task learning.

Multi-Task Learning

Domain Adaptation by Maximizing Population Correlation with Neural Architecture Search

no code implementations • 12 Sep 2021 • Zhixiong Yue, Pengxin Guo, Yu Zhang

Base on the PC function, we propose a new method called Domain Adaptation by Maximizing Population Correlation (DAMPC) to learn a domain-invariant feature representation for DA.

Domain Adaptation Neural Architecture Search

Multi-Objective Meta Learning

no code implementations • NeurIPS 2021 • Feiyang Ye, Baijiong Lin, Zhixiong Yue, Pengxin Guo, Qiao Xiao, Yu Zhang

Empirically, we show the effectiveness of the proposed MOML framework in several meta learning problems, including few-shot learning, neural architecture search, domain adaptation, and multi-task learning.

Domain Adaptation Few-Shot Learning +2

Effective, Efficient and Robust Neural Architecture Search

no code implementations • 19 Nov 2020 • Zhixiong Yue, Baijiong Lin, Xiaonan Huang, Yu Zhang

Although NAS methods can find network architectures with the state-of-the-art performance, the adversarial robustness and resource constraint are often ignored in NAS.

Adversarial Robustness Neural Architecture Search