14 citations · 19 across the 4 of their papers we have counts for
4 papers
Multi-task Learning by Leveraging the Semantic Information
Fan Zhou, Brahim Chaib-draa, Boyu Wang
One crucial objective of multi-task learning is to align distributions across tasks so that the information between them can be transferred and shared. However, existing approaches…
Beyond -Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence
Changjian Shui, Qi Chen, Jun Wen +3
We reveal the incoherence between the widely-adopted empirical domain adversarial training and its generally-assumed theoretical counterpart based on -divergence. Conc…
Discriminative Active Learning for Domain Adaptation
Fan Zhou, Changjian Shui, Bincheng Huang +2
Domain Adaptation aiming to learn a transferable feature between different but related domains has been well investigated and has shown excellent empirical performances. Previous w…
Deep Active Learning: Unified and Principled Method for Query and Training
Changjian Shui, Fan Zhou, Christian Gagné +1
In this paper, we are proposing a unified and principled method for both the querying and training processes in deep batch active learning. We are providing theoretical insights fr…