607 citations · 1.4k across the 17 of their papers we have counts for
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Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment Classification
Zheng Li, Ying Wei, Yu Zhang +3
Aspect-level sentiment classification (ASC) aims at identifying sentiment polarities towards aspects in a sentence, where the aspect can behave as a general Aspect Category (AC) or…
Learning to Multitask
Yu Zhang, Ying Wei, Qiang Yang
Multitask learning has shown promising performance in many applications and many multitask models have been proposed. In order to identify an effective multitask model for a given…
Parameter Transfer Unit for Deep Neural Networks
Yinghua Zhang, Yu Zhang, Qiang Yang
Parameters in deep neural networks which are trained on large-scale databases can generalize across multiple domains, which is referred as "transferability". Unfortunately, the tra…
Cross-domain Dialogue Policy Transfer via Simultaneous Speech-act and Slot Alignment
Kaixiang Mo, Yu Zhang, Qiang Yang +1
Dialogue policy transfer enables us to build dialogue policies in a target domain with little data by leveraging knowledge from a source domain with plenty of data. Dialogue senten…
LCMR: Local and Centralized Memories for Collaborative Filtering with Unstructured Text
Guangneng Hu, Yu Zhang, Qiang Yang
Collaborative filtering (CF) is the key technique for recommender systems. Pure CF approaches exploit the user-item interaction data (e.g., clicks, likes, and views) only and suffe…
CoNet: Collaborative Cross Networks for Cross-Domain Recommendation
Guangneng Hu, Yu Zhang, Qiang Yang
The cross-domain recommendation technique is an effective way of alleviating the data sparse issue in recommender systems by leveraging the knowledge from relevant domains. Transfe…