Volume 51, Number 2, April-June 2017
|Page(s)||329 - 341|
|Published online||27 February 2017|
- S. Abe, Support Vector Machines for Pattern Classification. Advances in Pattern Recognition, 2nd edition. Springer, London, UK (2010).
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- K. Bennett and E. Bredensteiner, Duality and Geometry in SVMs, In Proc. of 17th International Conference on Machine Learning, edited by P. Langley. San Francisco (2000) 65–72.
- N. Couellan, S. Jan, T. Jorquera and J.-P. Georgé, Self Adaptive Support Vector Machine: A Multi-Agent Optimization Perspective. Expert Syst. Appl. 42 (2015) 4284–4298. [CrossRef]
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- N. Japkowicz and S. Stephen, The class imbalance problem: A systematic study. Intel. Data Anal. 6 (2002) 429–449.
- G. Koltsidas and F.-N. Pavlidou, A Game Theoretical Approach to Clustering of Ad-Hoc and Sensor Networks. Telecomm. Systems 47 (2011) 81–93. [CrossRef]
- D.G. Luenberger, Optimization by Vector Space Methods, 1st edition. John Wiley & Sons, Inc., New York, USA (1997)
- A. Neyman and S. Sorin (eds.), Stochastic Games and Applications, Proc. of the NATO Advanced Study Institute, Stony Brook, New York, USA, 1999, Series: Nato Science Series C: (closed), Vol. 570 (2003)
- S. Parsons and M. Wooldridge, Game Theory and Decision Theory in Multi-Agent Systems. Autonomous Agents and Multi-Agent Systems 5 (2002) 243–254. [CrossRef]
- M. Petrovskiy, A Game Theory Approach to Pairwise Classification with Support Vector Machines. Proc. of the 2004 International Conference on Machine Learning and Application. ICMLAs, IEEE Computer Society (2004) 115–122.
- B. Schölkopf and A. Smola, Learning with Kernels. MIT, Cambridge (2002).
- S. Sra, S. Nowozin and S.J. Wright, Optimization for Machine Learning. MIT Press, Cambridge (2011).
- G.M. Weiss, Mining with Rarity: A Unifying Framework. ACM SIGKDD Explorations Newsletter 6 (2004) 7–19. [CrossRef]
- G. Weiss, A modern Approach to Distributed Artifical Intelligence. Intelligent Robotics & Autonomous Agents Series, MIT Press, Cambridge (2000).
- J. Weston and C. Watkins, Support Vector Machines for Multi-Class Pattern Recognition. Proc. of ESANN’1999, Bruges, Belgium (1999) 219–224.
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