17 citations · 32 across the 8 of their papers we have counts for
8 papers
New Insights on Relieving Task-Recency Bias for Online Class Incremental Learning
Guoqiang Liang, Zhaojie Chen, Zhaoqiang Chen +2
To imitate the ability of keeping learning of human, continual learning which can learn from a never-ending data stream has attracted more interests recently. In all settings, the…
Active Deep Learning on Entity Resolution by Risk Sampling
Youcef Nafa, Qun Chen, Zhaoqiang Chen +4
While the state-of-the-art performance on entity resolution (ER) has been achieved by deep learning, its effectiveness depends on large quantities of accurately labeled training da…
Adaptive Deep Learning for Entity Resolution by Risk Analysis
Zhaoqiang Chen, Qun Chen, Youcef Nafa +4
The state-of-the-art performance on entity resolution (ER) has been achieved by deep learning. However, deep models are usually trained on large quantities of accurately labeled tr…
Towards Interpretable and Learnable Risk Analysis for Entity Resolution
Zhaoqiang Chen, Qun Chen, Boyi Hou +3
Machine-learning-based entity resolution has been widely studied. However, some entity pairs may be mislabeled by machine learning models and existing studies do not study the risk…
Gradual Machine Learning for Entity Resolution
Boyi Hou, Qun Chen, Yanyan Wang +2
Usually considered as a classification problem, entity resolution (ER) can be very challenging on real data due to the prevalence of dirty values. The state-of-the-art solutions fo…
Improving Machine-based Entity Resolution with Limited Human Effort: A Risk Perspective
Zhaoqiang Chen, Qun Chen, Boyi Hou +2
Pure machine-based solutions usually struggle in the challenging classification tasks such as entity resolution (ER). To alleviate this problem, a recent trend is to involve the hu…
r-HUMO: A Risk-Aware Human-Machine Cooperation Framework for Entity Resolution with Quality Guarantees
Boyi Hou, Qun Chen, Zhaoqiang Chen +2
Even though many approaches have been proposed for entity resolution (ER), it remains very challenging to find one with quality guarantees. To this end, we proposea risk-aware HUma…
Enabling Quality Control for Entity Resolution: A Human and Machine Cooperation Framework
Zhaoqiang Chen, Qun Chen, Fengfeng Fan +6
Even though many machine algorithms have been proposed for entity resolution, it remains very challenging to find a solution with quality guarantees. In this paper, we propose a no…