Zhiqiang Li

TL;DR: The authors survey almost 70 representative defect prediction papers in recent years, most of which are published in the prominent software engineering journals and top conferences, and identify some practical guidelines for both software engineering researchers and practitioners in future software defect prediction.

TL;DR: A novel multi- label dictionary learning approach, named multi-label dictionary learning (MLDL) with label consistency regularization and partial-identical label embedding MLDL, which conducts MLDL and partial -identicallabel embedding simultaneously.

TL;DR: A new cost-sensitive transfer kernel canonical correlation analysis (CTKCCA) approach for HDP can not only make the data distributions of source and target projects much more similar in the nonlinear feature space, where the learned features have favorable separability, but also utilize the different misclassification costs for defective and defect-free classes to alleviate the class imbalance problem.

TL;DR: This paper introduces the multi-view dictionary learning technique into the field of multi-spectral face recognition and proposes a multi-Spectral low-rank structured dictionary learning (MLSDL) approach, which learns multiple structured dictionaries, including a spectrum-common dictionary and multiple spectrum-specific dictionaries.

TL;DR: To utilize multiple sources effectively, a multi-source selection based manifold discriminant alignment (MSMDA) approach is proposed and results show that MSMDA can achieve better performance than a range of baseline methods.