16 citations · 32 across the 8 of their papers we have counts for
10 papers
Time-Series Domain Adaptation via Sparse Associative Structure Alignment: Learning Invariance and Variance
Zijian Li, Ruichu Cai, Jiawei Chen +4
Domain adaptation on time-series data is often encountered in the industry but received limited attention in academia. Most of the existing domain adaptation methods for time-serie…
REST: Debiased Social Recommendation via Reconstructing Exposure Strategies
Ruichu Cai, Fengzhu Wu, Zijian Li +4
The recommendation system, relying on historical observational data to model the complex relationships among the users and items, has achieved great success in real-world applicati…
Graph Domain Adaptation: A Generative View
Ruichu Cai, Fengzhu Wu, Zijian Li +3
Recent years have witnessed tremendous interest in deep learning on graph-structured data. Due to the high cost of collecting labeled graph-structured data, domain adaptation is im…
FRITL: A Hybrid Method for Causal Discovery in the Presence of Latent Confounders
Wei Chen, Kun Zhang, Ruichu Cai +4
We consider the problem of estimating a particular type of linear non-Gaussian model. Without resorting to the overcomplete Independent Component Analysis (ICA), we show that under…
Semi-Supervised Disentangled Framework for Transferable Named Entity Recognition
Zhifeng Hao, Di Lv, Zijian Li +3
Named entity recognition (NER) for identifying proper nouns in unstructured text is one of the most important and fundamental tasks in natural language processing. However, despite…
Time Series Domain Adaptation via Sparse Associative Structure Alignment
Ruichu Cai, Jiawei Chen, Zijian Li +6
Domain adaptation on time series data is an important but challenging task. Most of the existing works in this area are based on the learning of the domain-invariant representation…