Books and Proceedings
 Y. Gao and N. Japkowicz (Eds.) Lecture Notes in Computer Science 5549, Springer.
 Advances in Artificial Intelligence  Proceedings of the 22^{nd} Canadian Conference on Artificial Intelligence.
 W. Zhang, S. Li, Z. Wang, and Yong Gao. (Foundations of Modern Mathematics Series, Vol 116, Science Press China
 Introduction to MultiValued Stochastic Processes (First Edition, 1996; Second Edition, 2007).
Artificial Intelligence and Knowledge Discovery
 Y. Gao.
The 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
 A Random Model for Argumentation Framework: Phase Transitions, Empirical Hardness, and Heuristics.
 P. Zhang and Y. Gao.
Theoretical Computer Science, 2017.
 A Probabilistic Study of Generalized Solution Concepts in SAT and Constraint Programming.
 Y. Gao. Artificial Intelligence, 2009.
 Data Reductions, Fixed Parameter Tractability, and Random Weighted dCNF Satisfiability.
 Y. Gao and J. Culberson. Journal of Artificial Intelligence Research, 2007.
 Consistency and Random Constraint Satisfaction Problems.
 Y. Pei, O. Zaiane and Y. Gao. The 6th IEEE International Conference on Data Mining (ICDM'06).
 An Efficient Referencebased Approach to Outlier Detection in Large Dataset.
 Y. Gao and J. Culberson. Evolutionary Computation, 2005.
 Space Complexity of Estimation of Distribution Algorithms.
 J. Culberson, Y. Gao and C. Anton.
The 19th International Joint Conference on Artificial IntelligenceIJCAI'05)
 Phase Transitions of Dominating Clique Problem and Their Implications to Heuristics in Satisfiability Search.
 Y. Gao.
The 19th Conference on Uncertainty in Artificial Intelligence(UAI'03).
 Phase Transition of Tractability in Constraint Satisfaction and Bayesian Network Inference.
 Y. Leung, Y.Gao, and Z. Xu. IEEE Transactions on Neural Networks, 1997.
 Degree of Population Diversity: A Perspective on Premature Convergence in Genetic Algorithms and its Markov Chain Analysis.



Network Science and Graph Theory
 S. Jia, L. Gao, Y. Gao, J. Nastos, et al.
IEEE Access, 2018
 Viewing the MesoScale Structures in ProteinProtein Interaction Networks Using 2Clubs
 Congsong Zhang and Yong Gao. The 23^{rd} Annual Intern. Computing and Combinatorics Conference
(COCOON'17)
 On the Complexity of kMetric Antidimension Problem and the Szie of
kAntiresolving Sets in Random Graphs
 S. Jia, L. Gao, Y. Gao, J. Nastos, et al.
New Journal of Physics, 2015.
 Defining and Identifying Cograph Communities in Complex Networks.
 B. Wang, L. Gao, Y. Gao, Y. Deng, and Y. Wang. Scientific Reports, 2014.
 Controllability and Observability Analysis for Vertex Domination Centrality in Directed Networks.
 J. Nastos and Y. Gao. Social Networks, 2013.
 Familial Groups in Social Networks.
 Y. Gao, D. Hare, and J. Nastos. Discrete Mathematics, 2013.
 The Cluster Deletion Problem for Cographs.
 A. Sridharan, Yong Gao, K. Wu, and J. Nastos. IEEE INFOCOM'11
 Statistical behavior of embeddedness and community of overlapping cliques in online social networks.
 Y. Gao. Theoretical Computer Science, 2009.
 The Degree Distribution of Random kTrees.
 K. Wu, Y. Gao, F. Li, and Y. Xiao. Mobile Networks and Applications, 2005.
 Lightweight DeploymentAware Scheduling for Wireless Sensor Networks.


Discrete Mathematics and Theoretical Computer Science
 Y. Gao, D. Hare, and J. Nastos. Discrete Applied Mathematics, 2013.
 The Parameterized Complexity of Graph Diameter Augmentation.
 J. Nastos and Y. Gao. Discrete Mathematics, Algorithms and Applications,, 2012.
[Preprint at arXiv.org]
 Bounded Search Tree Algorithms for Parameterized Cograph Deletion: Efficient Branching Rules by Exploitng Structures of Special Graph Classes.
 Y. Gao. Discrete Applied Mathematics.,
2012. [Preprint, 2011 Revision] [arXiv.org version]
 Treewidth of ErdosRenyi Random Graphs, Random Intersection Graphs, and ScaleFree Random Graphs.
 Y. Gao. Journal of Discrete Algorithms, 2009.
[PDF]
 Threshold Dominating Cliques in Random Graphs and Interval Routing.
 Y. Gao and J. Culberson. Discrete
Applied Mathematics, 2005
 Resolution complexity of random constraint satisfaction problems: Another half of the story.
 Z. Chen, Y. Gao, G. H. Lin, et al. Theoretical Computer Science, 2004.
 A Spaceefficient Algorithm for Sequence Alignment with Inversions and Reversals.


October 23, 2018, 4:29 am(54.80.188.87)

