activity
20182020
collaborators

6 papers

cs.LG2020

Comprehensible Counterfactual Explanation on Kolmogorov-Smirnov Test

Zicun Cong, Lingyang Chu, Yu Yang +1

The Kolmogorov-Smirnov (KS) test is popularly used in many applications, such as anomaly detection, astronomy, database security and AI systems. One challenge remained untouched is…

cs.DS2019

Finding Route Hotspots in Large Labeled Networks

Mingtao Lei, Xi Zhang, Lingyang Chu +3

In many advanced network analysis applications, like social networks, e-commerce, and network security, hotspots are generally considered as a group of vertices that are tightly co…

cs.LG2019

Exact and Consistent Interpretation of Piecewise Linear Models Hidden behind APIs: A Closed Form Solution

Zicun Cong, Lingyang Chu, Lanjun Wang +2

More and more AI services are provided through APIs on cloud where predictive models are hidden behind APIs. To build trust with users and reduce potential application risk, it is…

cs.DB2018

Mining Top-k Sequential Patterns in Database Graphs:A New Challenging Problem and a Sampling-based Approach

Mingtao Lei, Lingyang Chu, Zhefeng Wang

In many real world networks, a vertex is usually associated with a transaction database that comprehensively describes the behaviour of the vertex. A typical example is the social…

cs.SI2018

Mining Density Contrast Subgraphs

Yu Yang, Lingyang Chu, Yanyan Zhang +3

Dense subgraph discovery is a key primitive in many graph mining applications, such as detecting communities in social networks and mining gene correlation from biological data. Mo…

cs.CV2018

Exact and Consistent Interpretation for Piecewise Linear Neural Networks: A Closed Form Solution

Lingyang Chu, Xia Hu, Juhua Hu +2

Strong intelligent machines powered by deep neural networks are increasingly deployed as black boxes to make decisions in risk-sensitive domains, such as finance and medical. To re…