His scientific interests lie mostly in Data mining, Intrusion detection system, Artificial intelligence, Network security and Computer security. His Data mining research includes elements of Data modeling, Change detection, Affinity propagation and Cluster analysis. His studies in Artificial intelligence integrate themes in fields like Machine learning and Pattern recognition.
His study in the field of Probabilistic classification also crosses realms of Social discrimination. His Network security study which covers Anomaly detection that intersects with Support vector machine. The concepts of his Computer security study are interwoven with issues in Protocol and False positive rate.
Xiangliang Zhang spends much of his time researching Artificial intelligence, Data mining, Machine learning, Theoretical computer science and Cluster analysis. The study incorporates disciplines such as Graph and Pattern recognition in addition to Artificial intelligence. His Data mining research includes themes of Data modeling, Change detection and Data set.
He interconnects Crowdsourcing and Process in the investigation of issues within Machine learning. His research investigates the connection between Theoretical computer science and topics such as Graph that intersect with problems in Algorithm. His Intrusion detection system study combines topics from a wide range of disciplines, such as Anomaly detection and Network security.
Xiangliang Zhang mainly focuses on Artificial intelligence, Machine learning, Theoretical computer science, Deep learning and Graph. His study in Hypergraph extends to Artificial intelligence with its themes. As part of his studies on Machine learning, Xiangliang Zhang often connects relevant areas like Crowdsourcing.
The Theoretical computer science study combines topics in areas such as Node, Embedding, Representation and Relation. His Deep learning study incorporates themes from Matching, Algorithm, Probabilistic logic and Convolutional neural network. His work carried out in the field of Graph brings together such families of science as Inference, Graph, Node, Convolution and Key.
Xiangliang Zhang mainly investigates Artificial intelligence, Machine learning, Benchmark, Data science and Natural language processing. Xiangliang Zhang has included themes like Algorithm, Process and Graph in his Artificial intelligence study. His Algorithm research incorporates elements of Estimator, Probabilistic logic and Residual neural network.
He focuses mostly in the field of Graph, narrowing it down to matters related to Pattern recognition and, in some cases, Embedding. His multidisciplinary approach integrates Machine learning and Multi instance multi label in his work. His Benchmark study integrates concerns from other disciplines, such as Redundancy, Human–computer interaction and Reinforcement learning.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
CreditCoin: A Privacy-Preserving Blockchain-Based Incentive Announcement Network for Communications of Smart Vehicles
Lun Li;Jiqiang Liu;Lichen Cheng;Shuo Qiu.
IEEE Transactions on Intelligent Transportation Systems (2018)
Exploring Permission-Induced Risk in Android Applications for Malicious Application Detection
Wei Wang;Xing Wang;Dawei Feng;Jiqiang Liu.
IEEE Transactions on Information Forensics and Security (2014)
An up-to-date comparison of state-of-the-art classification algorithms
Chongsheng Zhang;Changchang Liu;Xiangliang Zhang;George Almpanidis.
Expert Systems With Applications (2017)
Decision Theory for Discrimination-Aware Classification
Faisal Kamiran;Asim Karim;Xiangliang Zhang.
international conference on data mining (2012)
Detecting Android malicious apps and categorizing benign apps with ensemble of classifiers
Wei Wang;Yuanyuan Li;Xing Wang;Jiqiang Liu.
Future Generation Computer Systems (2018)
Processing of massive audit data streams for real-time anomaly intrusion detection
Wei Wang;Xiaohong Guan;Xiangliang Zhang.
Computer Communications (2008)
Autonomic intrusion detection
Wei Wang;Thomas Guyet;René Quiniou;Marie-Odile Cordier.
Knowledge Based Systems (2014)
Profiling program behavior for anomaly intrusion detection based on the transition and frequency property of computer audit data
Wei Wang;Xiaohong Guan;Xiangliang Zhang;Liwei Yang.
Computers & Security (2006)
Data Streaming with Affinity Propagation
Xiangliang Zhang;Cyril Furtlehner;Michèle Sebag.
european conference on machine learning (2008)
Attribute Normalization in Network Intrusion Detection
Wei Wang;Xiangliang Zhang;Sylvain Gombault;Svein J. Knapskog.
international symposium on pervasive systems, algorithms, and networks (2009)
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