67 citations · 101 across the 10 of their papers we have counts for
10 papers
Generalizing across Temporal Domains with Koopman Operators
Qiuhao Zeng, Wei Wang, Fan Zhou +7
In the field of domain generalization, the task of constructing a predictive model capable of generalizing to a target domain without access to target data remains challenging. Thi…
Hessian Aware Low-Rank Perturbation for Order-Robust Continual Learning
Jiaqi Li, Yuanhao Lai, Rui Wang +7
Continual learning aims to learn a series of tasks sequentially without forgetting the knowledge acquired from the previous ones. In this work, we propose the Hessian Aware Low-Ran…
Foresee What You Will Learn: Data Augmentation for Domain Generalization in Non-stationary Environment
Qiuhao Zeng, Wei Wang, Fan Zhou +2
Existing domain generalization aims to learn a generalizable model to perform well even on unseen domains. For many real-world machine learning applications, the data distribution…
Evolving Domain Generalization
William Wei Wang, Gezheng Xu, Ruizhi Pu +6
Domain generalization aims to learn a predictive model from multiple different but related source tasks that can generalize well to a target task without the need of accessing any…
Gap Minimization for Knowledge Sharing and Transfer
Boyu Wang, Jorge Mendez, Changjian Shui +5
Learning from multiple related tasks by knowledge sharing and transfer has become increasingly relevant over the last two decades. In order to successfully transfer information fro…
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…
Domain Generalization via Optimal Transport with Metric Similarity Learning
Fan Zhou, Zhuqing Jiang, Changjian Shui +2
Generalizing knowledge to unseen domains, where data and labels are unavailable, is crucial for machine learning models. We tackle the domain generalization problem to learn from m…
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…