3 citations · 5 across the 3 of their papers we have counts for
5 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…
An Influence-based Approach for Root Cause Alarm Discovery in Telecom Networks
Keli Zhang, Marcus Kalander, Min Zhou +2
Alarm root cause analysis is a significant component in the day-to-day telecommunication network maintenance, and it is critical for efficient and accurate fault localization and f…
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…
Mixed Set Domain Adaptation
Sitong Mao, Keli Zhang, Fu-lai Chung
In the settings of conventional domain adaptation, categories of the source dataset are from the same domain (or domains for multi-source domain adaptation), which is not always tr…
An Improvement of PAA on Trend-Based Approximation for Time Series
Chunkai Zhang, Yingyang Chen, Ao Yin +4
Piecewise Aggregate Approximation (PAA) is a competitive basic dimension reduction method for high-dimensional time series mining. When deployed, however, the limitations are obvio…