Olvi L. Mangasarian
John von Neumann Professor Emeritus of Mathematics and Computer Sciences
Research Scientist Department of Mathematics, University of California, San Diego

Computer Sciences Department
University of Wisconsin
1210 W. Dayton St.
Madison, WI 53706-1685

Email: olvi at cs dot wisc dot edu
Interests: Optimization, data mining, classification & support vector machines


Currently not taking on post docs, interns or graduate students.


The research described here is supported by the National Science Foundation through grants CCR-0138308 and IIS-0511905, and the Data Mining Institute .


Talks Since 1998

Olvi Mangasarian
Unsupervised Classification via Convex Absolute Value Inequalities (PDF)
Center for Computational Mathematics Seminar
University of California at San Diego January 17, 2017.
Olvi Mangasarian & Glenn Fung
The Disputed Federalist Papers: Resolution via Support Vector Machine Feature Selection (PowerPoint)
Center for Computational Mathematics Seminar
University of California at San Diego January 21, 2014.
Olvi Mangasarian & Glenn Fung
Privacy Preserving Approximation (PowerPoint)
Center for Computational Mathematics Seminar
University of California at San Diego January 24, 2012.
Olvi Mangasarian
Privacy-Preserving Linear Programming (PowerPoint)
Center for Computational Mathematics Seminar
University of California at San Diego January 11, 2011.
Olvi Mangasarian & Glenn Fung
Proximal Support Vector Machine Classifiication (PowerPoint)
Center for Computational Mathematics Seminar
University of California at San Diego January 26, 2010.
Olvi Mangasarian & Edward Wild
Privacy-Preserving Support Vector Machine Classification via Random Kernels (PowerPoint)
International Symposium on Mathematical Programming 2009.
Chicago August 23-28, 2009.
Olvi Mangasarian & Edward Wild
Privacy-Preserving Support Vector Machines via Random Kernels (PowerPoint)
DMIN'08 The 4th International Conference on Data Mining
Las Vegas, Nevada July 14-17, 2008 DMIN08 Best Academic Research Paper Award.
Olvi Mangasarian & Edward Wild
Privacy-Preserving Support Vector Machine Classification via Random Kernels (PowerPoint)
Artificial Intelligence Research Talk
Computer Sciences Department, UW Madison February 20, 2008
Center for Computational Mathematics Seminar, Mathematics Department
University of California at San Diego, La Jolla April 7, 2009
Olvi Mangasarian & Edward Wild
Exact Differentiable Exterior Penalty for Linear Programming (PowerPoint)
Center for Computational Mathematics Seminar, Mathematics Department
University of California at San Diego, La Jolla February 12, 2008
Olvi Mangasarian & Edward Wild
Feature Selection in Nonlinear Kernel Classification (PowerPoint)
IEEE International Conference on Data Mining
Omaha, Nebraska
October 28, 2007
Olvi Mangasarian & Edward Wild
Knowledge-Based Breast Cancer Prognosis (PowerPoint) (pdf)
Computation & Informatics in Biology and Medicine (CIBM) Retreat
Pyle Center, Madison, Wisconsin
October 13, 2006
Olvi Mangasarian & Edward Wild
Nonlinear Knowledge in Kernel Machines (PowerPoint)
Data Mining and Mathematical Programming Workshop, University of Montreal, Quebec, Canada, October 10-13, 2006
Computational & Applied Mathematics Seminar, Mathematics Department
University of California at San Diego, La Jolla April 24, 2007
Olvi Mangasarian & Edward Wild
Feature Selection in Nonlinear Kernel Classification (PowerPoint)
Artificial Intelligence Seminar, University of Wisconsin, Madison, September 19, 2006
Olvi Mangasarian
Absolute Value Equation Solution via Concave Minimization (PowerPoint)
Computational & Applied Mathematics Seminar, Mathematics Department
University of California at San Diego, La Jolla April 11, 2006
Olvi Mangasarian & Edward Wild
Nonlinear Knowledge in Kernel Approximation (PowerPoint)
Joint Optimization/Artificial Intelligence Seminar, Computer Sciences Department
University of Wisconsin, Madison November 14, 2005
Computational & Applied Mathematics Seminar, Mathematics Department
University of California at San Diego, La Jolla January 24, 2006
Olvi Mangasarian & Edward Wild
Multiple Instance Learning via Successive Linear Programming (PowerPoint)
Computation & Informatics in Biology and Medicine (CIBM) Retreat
Pyle Center, Madison, Wisconsin
October 28, 2005
Olvi Mangasarian
Optimization in Data Mining (PowerPoint) (pdf)
International Conference on Continuous Optimization ICCOPT I, August 2-4, 2004, Rensselaer Polytechnic Institute Troy, New York. Computational and Applied Mathematics Seminar, Mathematics Department, University of California at San Diego, February 1, 2005.
Olvi Mangasarian & Edward Wild
Feature Selection in k-Median Clustering (PowerPoint)
Fourth SIAM International Conference on Data Mining (SDM 2004)
Workshop on Clustering in High Diemensional Data and its Applications
Lake Buena Vista, Florida, April 24, 2004.
Olvi Mangasarian, Jude Shavlik & Edward Wild
Knowledge-Based Kernel Approximation (PowerPoint)
Numerical Analysis Seminar, Mathematics Department, University of California at San Diego, January 13, 2004.
Glenn Fung, Olvi Mangasarian & Jude Shavlik
Knowledge-Based Nonlinear Support Vector Machine Classifiers (PowerPoint)
COLT 2003: The Sixteenth Annual Conference on Learning Theory and The Seventh Workshop on Kernel Machines Washington D.C. August 24-27, 2003. http://learningtheory.org/colt2003/
Y.-J. Lee, O. L. Mangasarian & W. H. Wolberg
Survival Time Classification of Breast Cancer Patients and Chemotherapy (PowerPoint)
Invited Talk, International Symposium on Mathematical Programming, Copenhagen, August 24-29, 2003.
Revised Talk (PowerPoint)
Computational & Applied Mathematics Seminar, Department of Mathematics, University of California at San Diego, April 19, 2005.
O. L. Mangasarian
Support Vector Machine Data Mining (PowerPoint)
Invited Talk, ExonHit Therapeutics, Paris, August 13, 2003.
O. L. Mangasarian
Support Vector Machines: Classification Algorithms and Applications (PowerPoint)
Scientific Computation Seminar, Mathematics Department, University of California at San Diego, February 4, 2003.
Glenn Fung, Olvi Mangasarian & Jude Shavlik
Knowledge-Based Support Vector Machine Classifiers (PowerPoint)
Neural Information Processing Systems NIPS*2002, Vancouver December 9-14, 2002.
G. Fung, O. L. Mangasarian & Alexnader J. Smola
Minimal Kernel Classifiers (PowerPoint)
INFORMS 2002, San Jose, California, November 17-20, 2002.
O. L. Mangasarian
Support Vector Machine Classification (PowerPoint)
Computation and Informatics in Biology and Medicine Retreat, Madison, November 15, 2002.
O. L. Mangasarian
A Newton Method for Linear Programming (PowerPoint)
Mathematics Department, University of California at San Diego, July 26, 2002.
G. Fung & O. L. Mangasarian
The Disputed Federalist Papers: SVM Feature Selection via Concave Minimization (PowerPoint)
CSNA 2002: Classification Society of North America Annual Meeting, Madison, Wisconsin, June 13-16, 2002.
O. L. Mangasarian
Support Vector Machines in Data Mining (PowerPoint)
AFOSR Systems & Software Annual Meeting, Syracuse, NY, June 3-7, 2002
G. Fung & O. L. Mangasarian
Incremental Support Vector Machine Classification (PowerPoint)
Second SIAM International Conference on Data Mining SDM 2002 Arlington, Virginia, April 11-13, 2002
G. Fung & O. L. Mangasarian
Proximal Support Vector Machine Classifiers (PowerPoint)
KDD 2001: Seventh ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
San Francisco August 26-29, 2001
O. L. Mangasarian
Data Mining with Support Vector Machines (PowerPoint)
IFIP 2001 System Modeling and Optimization Conference
Trier, Germany July 23 - 27, 2001
O. L. Mangasarian
Mathematical Programming for Support Vector Machines (PowerPoint)
INRIA
Rocquencourt, France July 17, 2001
Y.-J. Lee & O. L. Mangasarian
RSVM: Reduced Support Vector Machines (PowerPoint)
First SIAM International Conference on Data Mining
Chicago April 5-7, 2001. CD ROM Proceedings.
David R. Musicant & O. L. Mangasarian
LSVM: Lagrangian Support Vector Machines (PowerPoint)
NIPS 2000, Workshop on New Perspectives in Kernel-Based Learning Methods
Breckenridge, CO, December 1st, 2000
Glenn Fung & O. L. Mangasarian
Unlabeled Data Classification
INFORMS Annual Meeting, San Antonio, Texas, November 5-8, 2000.
O. L. Mangasarian
Mathematical Programming in Support Vector Machines (PowerPoint)
Video of Talk (RealVideo Stream)
HPCES (High Performance Computation for Engineering Systems) Seminar, MIT, October 4, 2000.
Glenn Fung & O. L. Mangasarian
Data Selection for Support Vector Machine Classification
(PowerPoint file here)
KDD-00 Knowledge Discovery and Data Mining, Boston, MA, August 20-23, 2000.
O. L. Mangasarian
Machine Learning & Data Mining via Support Vector Machines
(PowerPoint file here)
AFOSR Software & Systems Program Review, Marina Del Rey, CA, March 28-29, 2000
Y.-J. Lee, O. L. Mangasarian & W. H. Wolberg
Breast Cancer Survival Analysis and Chemotherapy via Generalized Support Vector Machines
Center for Discrete Mathematics and Theoretical Computer Science at Rutgers University (DIMACS), Workshop on Discrete Mathematical Problems with Medical Applications, December 8-10, 1999
David R. Musicant & O. L. Mangasarian
Massive Support Vector Regression.
(PowerPoint file here)
NIPS*99 Workshop on Learning with Support Vectors: Theory and Applications December 3, 1999.
Y.-J. Lee & O. L. Mangasarian
SSVM: A Smooth Support Vector Machine
Philadelphia INFORMS, November 7-10, 1999
O. L. Mangasarian & D. R. Musicant
Nonlinear Data Discrimination via Generalized Support Vector Machines
(PowerPoint file here - Philadelphia INFORMS, November 7-10, 1999)
ICCP99: International Conference on Complementarity Problems, Madison, Wisconsin, June 9-12, 1999
O. L. Mangasarian
Optimization in Machine Learning and Data Mining
Joint SIAM Annual Meeting & Optimization Conference, Atlanta, May 12, 1999.
Related SIAM News Article Volume 32, Number 10, December 1999 (pdf)
O. L. Mangasarian
Massive Data Discrimination via Generalized Support Vector Machines
AFOSR Software & Systems Program Review, Colorado Springs, February 3-4, 1999.
O. L. Mangasarian
Mathematical Programming in Machine Learning
NIPS*98 Workshop on Large Margin Classifiers, Breckenridge, Colorado, December 4-5, 1998.
O. L. Mangasarian & David R. Musicant
Successive Overrelaxation for Support Vector Machines
NIPS*98 Workshop on Mining Massive Databases, Breckenridge, Colorado, December 5, 1998.

Publications Since 1990

O. L. Mangasarian
Sufficient Conditions for the Unsolvability and Solvability of the Absolute Value Equation Data Mining Institute Technical Report 16-01, August 2016. Optimization Letters 11(7) 2017, 1469-1475.
G. M. Fung & O. L. Mangasarian
Unsupervised and Semisupervised Classification via Absolute Value Inequalities Data Mining Institute Technical Report 14-03, May 2014. Journal of Optimization Theory and Applications 168(2) 2016, 551-558.
O. L. Mangasarian
A Hybrid Algorithm for Solving the Absolute Value Equation Data Mining Institute Technical Report 14-02, April 2014. Optimization Letters 9(7) 2015, 1469-1474.
O. L. Mangasarian
Unsupervised Classification via Convex Absolute Value Inequalities Data Mining Institute Technical Report 14-01, March 2014. Optimization 64(1) 2015, 81-86.
O. L. Mangasarian
Linear Complementarity as Absolute Value Equation Solution Data Mining Institute Technical Report 13-02, March 2013. Optimization Letters 8(4) 2014, 1529-1534.
O. L. Mangasarian
Absolute Value Equation Solution via Linear Programming Data Mining Institute Technical Report 13-01, Februaty 2013. Journal of Optimization Theory and Applications 161, 870-876, 2014.
G. M. Fung and O. L. Mangasarian
Privacy-Preserving Linear and Nonlinear Approximation via Linear Programming
PDF Version
Data Mining Institute Technical Report 11-04, October 2011. Optimization Methods and Software 28(1), 207-216, 2013.
O. L. Mangasarian
Absolute Value Equation Solution via Dual Complementarity
PDF Version
Data Mining Institute Technical Report 11-03, September 2011. Optimization Letters 7(4), 2013, 625-630.
G. M. Fung and O. L. Mangasarian
Equivalence of Minimal 0-Norm and p-Norm Solutions of Linear Equalities, Inequalities and Linear Programs for Sufficiently Small p
PDF Version
Data Mining Institute Technical Report 11-02, April 2011. Journal of Optimization Theory and Applications 151, 2011, 1-10.
O. L. Mangasarian
Primal-Dual Bilinear Programming Solution of the AbsoluteValue Equation
PDF Version
Data Mining Institute Technical Report 11-01, February 2011. Optimization Letters 6(7), 1527-1533, 2012.
O. L. Mangasarian
Privacy-Preserving Horizontally-Partitioned Linear Programs
PDF Version
Data Mining Institute Technical Report 10-02, April 2010. Optimization Letters 6(3), 431-436, 2012.
Example of Security Breach Attempt
O. L. Mangasarian
Privacy-Preserving Linear Programming
PDF Version
Data Mining Institute Technical Report 10-01, March 2010. Optimization Letters 5, 165-172, 2011.
O. L. Mangasarian and Benjamin Recht
Probability of Unique Integer Solution to a System of Linear Equations
PDF Version
Data Mining Institute Technical Report 09-02, September 2009. European Journal of Operations Research 214 (2011) 27-30.
O. L. Mangasarian and M. C. Ferris
Uniqueness of Integer Solution of Linear Equations
PDF Version
Data Mining Institute Technical Report 09-01, July 2009. Optimization Letters 4, 559-565, 2010.
O. L. Mangasarian
Knapsack Feasibility as an Absolute Value Equation Solvable by Successive Linear Programming
PDF Version
Data Mining Institute Technical Report 08-03, September 2008. Optimization Letters 3(2) March 2009, 161-170. Online Version
O. L. Mangasarian and E. W. Wild
Privacy-Preserving Random Kernel Classification of Checkerboard Partitioned Data
PDF Version
Data Mining Institute Technical Report 08-02, September 2008. Annals of Information Systems XIII, 2010, 375-387.
O. L. Mangasarian
A Generalized Newton Method for Absolute Value Equations
PDF Version
Data Mining Institute Technical Report 08-01, May 2008. Optimization Letters 3(1), January 2009, 101-108. Online Version
O. L. Mangasarian and E. W. Wild
Privacy-Preserving Classification of Horizontally Partitioned Data via Random Kernels
PDF Version
Data Mining Institute Technical Report 07-03, November 2007. Proceedings of the 2008 International Conference on Data Mining DMIN08, Las Vegas July 2008, Volume II, 473-479, R. Stahlbock, S.V. Crone and S. Lessman, Editors.
DMIN08 Best Academic Research Paper Award.
O. L. Mangasarian, E. W. Wild and G. M. Fung
Privacy-Preserving Classification of Vertically Partitioned Data via Random Kernels
PDF Version
Data Mining Institute Technical Report 07-02, September 2007. ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 3, Number 2, 2008.
O. L. Mangasarian and E. W. Wild
Exactness Conditions for a Convex Differentiable Exterior Penalty for Linear Programming
PDF Version
Data Mining Institute Technical Report 07-01, July 2007. Optimization, Volume 60, Nos. 1-2, Jan-Feb 2011, 3-14.
O. L. Mangasarian and M. E. Thompson
Chunking for Massive Nonlinear Kernel Classification
PDF Version
Data Mining Institute Technical Report 06-07, December 2006. Optimization Methods and Software, 23, 2008, 365-274.
O. L. Mangasarian and E. W. Wild
Nonlinear Knowledge in Kernel Machines
PDF Version
Data Mining Institute Technical Report 06-06, November 2006. CRM Proceedings \& Lecture Notes, Volume 45, American Mathematical Society and Centre de Recherches Math\'{e}matiques at the Universit\'{e} de Montr\'{e}al, 2008, 181-198.
O. L. Mangasarian, E. W. Wild and G. M. Fung
Proximal Knowledge-Based Classification
PDF Version
Data Mining Institute Technical Report 06-05, November 2006. Statistical Analysis and Data Mining 1(4) 2009, 215-222.
O. L. Mangasarian & E. W. Wild
Nonlinear Knowledge-Based Classification
PDF Version
Data Mining Institute Technical Report 06-04, August 2006. IEEE Transactions on Neural Networks 19, October 2008, 1826-1832.
O. L. Mangasarian & E. W. Wild
Feature Selection for Nonlinear Kernel Support Vector Machines
PDF Version
Data Mining Institute Technical Report 06-03, July 2006. IEEE Seventh International Conference on Data Mining (ICDM'07) October 28, 2007, Omaha, NE, Workshop Proceedings 231-236.
O. L. Mangasarian
Absolute Value Equation Solution via Concave Minimization
PDF Version
Data Mining Institute Technical Report 06-02, March 2006. Optimization Letters 1(1), 2007, 3-8.
O. L. Mangasarian and M. E. Thompson
Massive Data Classification via Unconstrained Support Vector Machines
PDF Version
Data Mining Institute Technical Report 06-01, March 2006. Journal of Optimization Theory and Applications 131(3), December 2006, 315-325.
O. L. Mangasarian and R. R. Meyer
Absolute Value Equations
PDF Version
Data Mining Institute Technical Report 05-06, December 2005. Linear Algebra and Its Applications 419 (2006) 359-367.
O. L. Mangasarian and E. W. Wild
Nonlinear Knowledge in Kernel Approximation
PDF Version
Data Mining Institute Technical Report 05-05, October 2005. Revised June 2006. IEEE Transactions on Neural Networks 18, January 2007, 300-306.
O. L. Mangasarian
Absolute Value Programming
PDF Version
Data Mining Institute Technical Report 05-04, September 2005. Computational Optimization and Applications 36(1), January 2007, 43-53.
Computational Optimization and Applications 2007 Best Paper Award. COAP (2008) 41:147-149.
O. L. Mangasarian
Exact 1-Norm Support Vector Machines via Unconstrained Convex Differentiable Minimization
PDF Version
Data Mining Institute Technical Report 05-03, August 2005. Revised January 2006. Journal of Machine Learning Research 7, 2006, 1517-1530.
O. L. Mangasarian and E. W. Wild
Multiple Instance Classification via Successive Linear Programming
PDF Version
Data Mining Institute Technical Report 05-02, May 2005. Journal of Optimization Theory and Applications 137(1), 2008, 555-568.
O. L. Mangasarian, J. B. Rosen and M. E. Thompson
Nonconvex Piecewise-Quadratic Underestimation for Global Minimization
PDF Version
Data Mining Institute Technical Report 05-01, March 2005, Journal of Global Optimization 34(4), 2006, 475-488.
O. L. Mangasarian and E. W. Wild
Multisurface Proximal Support Vector Classification via Generalized Eigenvalues
PDF Version
Data Mining Institute Technical Report 04-03, June 2004. Revised September 2004. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(1), 2006, 69-74.
"This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder."
O. L. Mangasarian, J. B. Rosen and M. E. Thompson
Convex Kernel Estimation of Functions with Multiple Local Minima
PDF Version
Data Mining Institute Technical Report 04-02, May 2004. Computational Optimization and Applications 34(1), 2006, 35-45.
O. L. Mangasarian and E. W. Wild
Feature Selection in k-Median Clustering
PDF Version
Data Mining Institute Technical Report 04-01, January 2004. SIAM International Conference on Data Mining, Workshop on Clustering High Dimensional Data and its Applications, April 24, 2004, La Buena Vista, FL, Proceedings, pages 23-28.
G. M. Fung and O. L. Mangasarian
Breast Tumor Susceptibility to Chemotherapy via Support Vector Machines
PDF Version
Data Mining Institute Technical Report 03-06, November 2003. Computational Management Science 3, 2006, 103-112.
O. L. Mangasarian, J. W. Shavlik and E. W. Wild
Knowledge-Based Kernel Approximation
PDF Version
Data Mining Institute Technical Report 03-05, October 2003. Journal of Machine Learning Research 5, 1127-1141, 2004.
O. L. Mangasarian
Knowledge-Based Linear Programming
PDF Version
Data Mining Institute Technical Report 03-04, July 2003. SIAM Journal on Optimization 15, 2005, 375-382.
O. L. Mangasarian, J. B. Rosen and M. E. Thompson
Global Minimization via Piecewise-Linear Underestimation
PDF Version
Data Mining Institute Technical Report 03-03, June 2003. Journal of Global Optimization 32, 2005, 1-9.
G. M. Fung, O. L. Mangasarian and J. W. Shavlik
Knowledge-Based Nonlinear Kernel Classifiers
PDF Version
Data Mining Institute Technical Report 03-02, March 2003. Conference On Learning Theory (COLT 03) and Workshop on Kernel Machines, Washington, D.C., August 24 - 27, 2003. Proceedings edited by Manfred Warmuth and Bernhard Sch\"olkopf, Springer Verlag, Berlin, 2003, 102-113.
O. L. Mangasarian
Support Vector Machine Classification via Parameterless Robust Linear Programming
PDF Version
Data Mining Institute Technical Report 03-01, March 2003. Optimization Methods and Software 20, 2005, 115-125.
Glenn Fung and O. L. Mangasarian
A Feature Selection Newton Method for Support Vector Machine Classification
PDF Version
Data Mining Institute Technical Report 02-03, September 2002. Computational Optimization and Applications 28(2) 185-202, 2004.
O. L. Mangasarian
A Newton Method for Linear Programming
PDF Version
Data Mining Institute Technical Report 02-02, March 2002. Revised December 2002. Journal of Optimization Theory and Applications 121, 2004, 1-18. MATLAB Files
G. Fung and O. L. Mangasarian
Finite Newton Method for Lagrangian Support Vector Machine Classification
PDF Version
Data Mining Institute Technical Report 02-01, February 2002. Neurocomputing 55, September 2003, 39-55.
O. L. Mangasarian
A Finite Newton Method for Classification
PDF Version
Data Mining Institute Technical Report 01-11, December 2001. Optimization Methods and Software 17, 2002, 913-929.
O. L. Mangasarian
Set Containment Characterization
PDF Version
Data Mining Institute Technical Report 01-10, November 2001. Journal of Global Optimization 24(4) December 2002, 473-480.
Glenn Fung, O. L. Mangasarian and Jude Shavlik
Knowledge-Based Support Vector Machine Classifiers
PDF Version
Data Mining Institute Technical Report 01-09, November 2001. Neural Information Processing Systems 2002 (NIPS 2002), Vancouver, BC, December 10-12, 2002. ``Neural Information Processing Systems 15", S. Becker, S. Thrun and K. Obermayer, editors, MIT Press, Cambridge, MA, 2003, 521-528.
G. Fung and O. L. Mangasarian
Incremental Support Vector Machine Classification
PDF Version
Data Mining Institute Technical Report 01-08, September 2001. Proceedings of the Second SIAM International Conference on Data Mining, Arlington, Virginia, April 11-13, 2002,R. Grossman, H. Mannila and R. Motwani (editors), SIAM, Philadelphia 2002, 247-260.
G. Fung and O. L. Mangasarian
Multicategory Proximal Support Vector Machine Classifiers
PDF Version
Data Mining Institute Technical Report 01-06, July 2001. Machine Learning 59, 2005, 77-97.
O. L. Mangasarian
Data Mining via Support Vector Machines
PDF Version
Data Mining Institute Technical Report 01-05, May 2001. IFIP Conference on System Modelling and Optimization, Trier, Germany, July 23-27, 2001. ``System Modeling and Optimization XX", E. W. Sachs and R. Tichatschke, editors, Kluwer Academic Publishers, Boston 2003, 91-112.
Y.-J. Lee, O. L. Mangasarian and W. H. Wolberg
Survival-Time Classification of Breast Cancer Patients
PDF Version
Data Mining Institute Technical Report 01-03, March 2001. Computational Optimization and Applications 25, 2003, 151-166.
Glenn Fung and O. L. Mangasarian
Proximal Support Vector Machine Classifiers
PDF Version
Data Mining Institute Technical Report 01-02, February 2001. Proceedings KDD-2001, San Francisco August 26-29, 2001. Association for Computing Machinery, New York, 2001, 77-86.
Glenn Fung, O. L. Mangasarian & Alexander J. Smola
Minimal Kernel Classifiers
PDF Version
Data Mining Institute Technical Report 00-08, November 2000. Journal of Machine Learning Research 3, 2002, 303-321. http://www.ai.mit.edu/projects/jmlr/
Yuh-Jye Lee and O. L. Mangasarian
RSVM: Reduced Support Vector Machines
PDF Version
Data Mining Institute Technical Report 00-07, July 2000. CD Proceedings of the SIAM International Conference on Data Mining, Chicago, April 5-7, 2001, SIAM, Philadelphia, ISBN 0-89871-495-8.
O. L. Mangasarian and David R. Musicant
Lagrangian Support Vector Machines
PDF Version
Data Mining Institute Technical Report 00-06, June 2000.
Journal of Machine Learning Research 1, March 2001, 161-177.
Lagrangian Support Vector Machine web page with MATLAB code.
O. L. Mangasarian and David R. Musicant
Active Set Support Vector Machine Classification
Neural Information Processing Systems 2000 (NIPS 2000), Todd K. Lee, Thomas G. Dietterich and Volker Tresp, editors, MIT Press 2001, 577-583.
Active Support Vector Machine web page with MATLAB code.
G. Fung and O. L. Mangasarian
Data Selection for Support Vector Machine Classifiers
PDF Version
Data Mining Institute Technical Report 00-02, February 2000. "KDD-2000", Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 20-23, 2000, Boston, MA, R. Ramakrishnan & S. Stolfo, editors, ACM, NY 2000, 64-70.
Y.-J. Lee, O. L. Mangasarian and W. H. Wolberg
Breast Cancer Survival and Chemotherapy: A Support Vector Machine Analysis
Data Mining Institute Technical Report 99-10, December 1999. DIMACS Series in Discrete Mathematics and Theoretical Computer Science, Volume 55, American Mathematical Society 2000, 1-10.
O. L. Mangasarian and D. R. Musicant
Robust Linear and Support Vector Regression
PDF Version
Data Mining Institute Technical Report 99-09, November 1999. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 2000, 950-955.
Glenn Fung and O. L. Mangasarian
Semi-Supervised Support Vector Machines for Unlabeled Data Classification.
PDF Version
Data Mining Institute Technical Report 99-05, October 1999. Optimization Methods and Software 15, 2001, 29-44.
Alex J. Smola, Olvi L. Mangasarian and Bernhard Schoelkopf
Sparse Kernel Feature Analysis.
Data Mining Institute Technical Report 99-04, October 1999. 24th Annual Conference of Gesellschaft für Klassifikation, University of Passau, Passau, Germany March 15-17, 2000.
Y.-J. Lee and O. L. Mangasarian
SSVM: A Smooth Support Vector Machine for Classification
PDF Version
Data Mining Institute Technical Report 99-03, September 1999, Computational Optimization and Applications 20(1), October 2001, 5-22.
O. L. Mangasarian and David R. Musicant
Large Scale Kernel Regression via Linear Programming
PDF Version
Data Mining Institute Technical Report 99-02, August 1999, Machine Learning 46(1/3), 255-269, January 2002.
P. S. Bradley, O. L. Mangasarian and David R. Musicant
Optimization Methods in Massive Datasets.
Data Mining Technical Report 99-01, June 1999. "Handbook of Massive Datasets", J. Abello , P. M. Pardalos, M. G. C. Resende, editors, Kluwer Academic Publishers, 2002, 439-472.
O. L. Mangasarian and David R. Musicant
Data Discrimination via Nonlinear Generalized Support Vector Machines
Mathematical Programming Technical Report 99-03, March 1999. "Complementarity: Applications, Algorithms and Extensions", in M. C. Ferris, O. L. Mangasarian and J.-S. Pang, editors, Kluwer Academic Publishers, 2001, 233-251.
O. L. Mangasarian and David R. Musicant
Successive Overrelaxation for Support Vector Machines.
Mathematical Programming Technical Report 98-18, November 1998. IEEE Transactions on Neural Networks, 10, September 1999, 1032-1037.
O. L. Mangasarian
Generalized Support Vector Machines (Technical Report Version) PDF Version (MIT Press Version)
Mathematical Programming Technical Report 98-14, October 1998. "Advances in Large Margin Classifiers", A. J. Smola, P. Bartlett, B. Sch\"{o}kopf and D. Schuurmans, editors, MIT Press, 2000, 135-146.
P. S. Bradley & O. L. Mangasarian
k-Plane Clustering.
Mathematical Programming Technical Report 98-08, August 1998. Journal of Global Optimization 16, Number 1, 2000, 23-32.
P. S. Bradley & O. L. Mangasarian
Massive Data Discrimination via Linear Support Vector Machines.
Mathematical Programming Technical Report 98-05, May 1998. Revised March 31, 1999. Optimization Methods and Software, 13(1), 2000, 1-10.
P. S. Bradley & O. L. Mangasarian
Feature Selection via Concave Minimization and Support Vector Machines.
Mathematical Programming Technical Report 98-03, February 1998. "Machine Learning Proceedings of the Fifteenth International Conference(ICML '98)", J. Shavlik, editor, Morgan Kaufmann, San Francisco, California, 82-90, 1998.
P. S. Bradley, Usama M. Fayyad & O. L. Mangasarian
Mathematical Programming for Data Mining: Formulations and Challenges.
PDF Version
Mathematical Programming Technical Report 98-01, January 1998. Revised July 1998 . INFORMS Journal on Computing 11, 1999, 217-238.
O. L. Mangasarian
Regularized Linear Programs with Equilibrium Constraints.
Mathematical Programming Technical Report 97-13, November 1997. In "Reformulation-Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods", M. Fukushima and Liqun Qi, editors, Kluwer Academic Publishers, 1998, 259-268.
P. S. Bradley & O. L. Mangasarian
Parsimonious Side Propagation,
Mathematical Programming Technical Report 97-11, October 1997. In "ICASSP98: IEEE International Conference on Acoustics, Speech and Signal Processing, Seattle May 12-15, 1998, Volume 3, pages 1873-1876.
O. L. Mangasarian
Polyhedral Boundary Projection.
Mathematical Programming Technical Report 97-10, October 1997, SIAM Journal on Optimization 9, 1999, 1128-1134.
O. L. Mangasarian
Arbitrary-Norm Separating Plane.
Mathematical Programming Technical Report 97-07, May 1997.
O. L. Mangasarian
Arbitrary-Norm Separating Plane.
Mathematical Programming Technical Report 97-07r, May 1997, Revised September 1998. Operations Research Letters 24, 1999, 15-23.
O. L. Mangasarian
Minimum-Support Solutions of Polyhedral Concave Programs
Mathematical Programming Technical Report 97-05, April 1997. Revised March 1998, Optimization 45, 1999, 149-162.
P. S. Bradley, O. L. Mangasarian and J. B. Rosen
Parsimonious Least Norm Approximation
Mathematical Programming Technical Report 97-03, March 1997. Computational Optimization and Applications 11(1), October 1998, 5-21.
O. L. Mangasarian
Solution of General Linear Complementarity Problems via Nondifferentiable Concave Minimization.
Mathematical Programming Technical Report 96-10, November 1996, Acta Mathematica Vietnamica, 22(1), 1997, 199-205.
O. L. Mangasarian and M. V. Solodov
A Linearly Convergent Derivative-Free Descent Method for Strongly Monotone Complementarity Problems.
Mathematical Programming Technical Report 96-07, October 1996, Computational Optimization & Applications 14, 1999, 5-16.
O. L. Mangasarian and Jong-Shi Pang
Exact Penalty Functions for Mathematical Programs with Linear Complementarity Constraints.
Mathematical Programming Technical Report 96-06, August 1996, Optimization 42(1), 1997, 1-8.
O. L. Mangasarian
Mathematical Programming in Data Mining
Mathematical Programming Technical Report 96-05, August 1996 -- Revised November 1996 and March 1997, Data Mining and Knowledge Discovery, 1(2), 1997, 183-201.
O. L. Mangasarian
Error Bounds for Nondifferentiable Convex Inequalities under a Strong Slater Constraint Qualification.
Mathematical Programming Technical Report 96-04, July 1996. Revised March 1997, Mathematical Programming, 83, 1998, 187-194.
P. S. Bradley, O. L. Mangasarian and W. N. Street
Clustering via Concave Minimization.
Mathematical Programming Technical Report 96-03, May 1996. Advances in Neural Information Processing Systems 9, MIT Press, Cambridge, MA 1997, 368-374.
W. N. Street, O. L. Mangasarian and W. H. Wolberg
Individual and Collective Prognostic Prediction.
Mathematical Programming Technical Report 96-01, January 1996.
P. S. Bradley, O. L. Mangasarian and W. N. Street
Feature Selection via Mathematical Programming.
Mathematical Programming Technical Report 95-21, December 1995. INFORMS Journal on Computing 10, 1998, 209-217.
O. L. Mangasarian
Machine Learning via Polyhedral Concave Minimization.
Mathematical Programming Technical Report 95-20, November 1995. "Applied Mathematics and Parallel Computing -- Festschrift for Klaus Ritter", H. Fischer, B. Riedmueller, S. Schaeffler, editors, Physica-Verlag, Germany 1996, 175-188.
O. L. Mangasarian
The Ill-Posed Linear Complementarity Problem.
Mathematical Programming Technical Report 95-15, August 1995, Revised November 1995. "Complementarity and Variational Problems", M. C. Ferris and J.-S. Pang, editors, SIAM, Philadelphia, PA, 1997, 226-233.
W. Nick Street and O. L. Mangasarian
Improved Generalization via Tolerant Training.
Mathematical Programming Technical Report 95-11, July 1995. Journal of Optimization Theory and Applications, 96(2), February 1998, 259-279.
O. L. Mangasarian
Mathematical Programming in Machine Learning.
Mathematical Programming Technical Report 95-06, April 1995, Revised July 1995 in "Nonlinear Optimization and Applications", G. Di Pillo and F. Giannessi, editors, Proceedings of Nonlinear Optimization and Applications Workshop, Erice, June 1995, Plenum Press, New York 1996, 283-295.
W. N. Street, O. L. Mangasarian and W. H. Wolberg
An inductive learning approach to prognostic prediction.
Proceedings of the Twelfth International Conference on Machine Learning, A. Prieditis and S. Russell, editors, San Francisco, 522-530, 1995.
Chunhui Chen and O. L. Mangasarian
Hybrid Misclassification Minimization.
Mathematical Programming Technical Report 95-05, February 1995, Revised July 1995 and August 1995. Advances in Computational Mathematics 5(2) 1996, 127-136.
O. L. Mangasarian
Optimization in Machine Learning.
Mathematical Programming Technical Report 95-01, January 1995. SIAG/OPT Views-and-News 6, 1995, 3-7.
W. H. Wolberg, W. N. Street and O. L. Mangasarian
Computerized breast cancer diagnosis from fine needle aspirates.
Archives of Surgery 130, 511-516, 1995.
Chunhui Chen and O. L. Mangasarian
A Class of Smoothing Functions for Nonlinear and Mixed Complementarity Problems.
Mathematical Programming Technical Report 94-11, August 1994. Revised October 1994, February 1995 and September 1995. Computational Optimization and Applications 5, 1996, 97-138.
O. L. Mangasarian, W. Nick Street and W. H. Wolberg
Breast Cancer Diagnosis and Prognosis via Linear Programming.
Mathematical Programming Technical Report 94-10, August 1994. Revised December 1994. Operations Research 43(4), July-August 1995, 570-577.
O. L. Mangasarian
The Linear Complementarity Problem as a Separable Bilinear Program.
Mathematical Programming Technical Report 94-09, July 1994. Journal of Global Optimization 6, 1995, 153-161.
O. L. Mangasarian and M. V. Solodov
Backpropagation Convergence via Deterministic Nonmonotone Perturbed Minimization.
Mathematical Programming Technical Report 94-06, June 1994. Advances in Neural Information Processing Systems 6, (J. D. Cowan, G. Tesauro and J. Alspector, editors) 383-390, Morgan Kaufmann Publishers, San Francisco, California 1994.
Chunhui Chen and O. L. Mangasarian
Smoothing Methods for Convex Inequalities and Linear Complementarity Problems.
Computer Sciences Technical Report 1191r, November 1993. Revised November 1994. Mathematical Programming 71, 1995, 51-69.
O. L. Mangasarian and J.-S. Pang
The Extended Linear Complementarity Problem.
Computer Sciences Technical Report 1188, November 1993. SIAM Journal on Matrix Analysis and Applications 16, 1995, 359-368.
O. L. Mangasarian
Misclassification Minimization.
Computer Sciences Technical Report 1186, October 1993. Revised September 1994. Journal of Global Optimization 5(4), December 1994, 309-323.
O. L. Mangasarian
Error Bounds for Inconsistent Linear Inequalities and Programs.
Computer Sciences Technical Report 1166, July 1993. Operations Research Letters 15, May 1994, 187-192.
O. L. Mangasarian and M. V. Solodov
Serial and Parallel Backpropagation for Neural Nets via Nonmonotone Perturbed Minimization.
Computer Sciences Technical Report 1149r, April 1993. Revised December 1993. Optimization Methods and Software 4, 1994, 103-116.
O. L. Mangasarian
Parallel Gradient Distribution in Unconstrained Optimization.
Computer Sciences Technical Report 1145, 1993. SIAM Journal on Control and Optim ization 33(6), 1995, 1916-1925.
W. N. Street, W. H. Wolberg and O. L. Mangasarian
Nuclear feature extraction for breast tumor diagnosis.
IS&E/SPIE 1993 International Symposium on Electronic Imaging: Science and Technology, Volume 1905, pages 861-870, San Jose, California, 1993.
O. L. Mangasarian
Mathematical Programming in Neural Networks.
Computer Sciences Technical Report 1129, 1992. ORSA Journal on Computing 5, 1993, 349-360.
K. P. Bennett and O. L. Mangasarian
Multicategory Discrimination via Linear Programming.
Computer Sciences Technical Report 1127, 1992. Optimization Methods and Software 3, 1994, 27-39.
W. H. Wolberg, W. N. Street and O. L. Mangasarian
Breast cytology diagnosis with digital image analysis.
Analytical and Quantitative Cytology and Histology 15(6), 1993, 396-404
K. P. Bennett and O. L. Mangasarian
Bilinear Separation of Two Sets in n-Space.
Computer Sciences Technical Report 1109, 1992. Computational Optimization and Applications 2, 1993, 207-227.
O. L. Mangasarian and M. V. Solodov
Nonlinear Complementarity as Unconstrained and Constrained Minimization.
Computer Sciences Technical Report 1074, 1992. Mathematical Programming, Series B, 62, 1993, 277-297.
Michael C. Ferris and Olvi L. Mangasarian
Error Bounds and Strong Upper Semicontinuity for Monotone Affine Variational Inequalities.
Computer Sciences Technical Report 1056a, 1991. Annals of Operations Research, 47, 1993, 293-305.
K. P. Bennett and O. L. Mangasarian
Robust Linear Programming Discrimination of Two Linearly Inseparable Sets.
Computer Sciences Technical Report 1054a, 1991. Optimization Methods and Software 1, 1992, 23-34.
Michael C. Ferris and O. L. Mangasarian
Parallel Constraint Distribution.
Computer Sciences Technical Report 971, 1990. SIAM Journal on Optimization 1, 1991, 487-500.
O. L. Mangasarian, R. Setiono and W. H. Wolberg
Pattern recognition via linear programming :theory and application to medical diagnosis.
Computer Sciences Technical Report 878, 1989."Large-Scale Numerical Optimization ", T. F. Coleman and Y. Li, editors, SIAM, Philadelphia, Pennsylvania 1990, 22-3 1.

Some Publications Prior to 1990

O. L. Mangasarian
A Simple Characterization of Solution Sets of Convex Programs.
Computer Sciences Technical Report 685r, 1987. Operations Research Letters 7, 1988, 21-26.
O. L. Mangasarian and T.-H. Shiau
Variable Complexity Norm Maximization Problem
SIAM Journal on Algebraic and Discrete Methods 7(3), 1986, 455-461.
O. L. Mangasarian and R. R. Meyer
Nonlinear Perturbation of Linear Programs
SIAM Journal on Control and Optimization 17(6), 1979, 745-752.
O. L. Mangasarian and S. Fromovitz
The Fritz John Necessary Optimality Conditions in the Presence of Equality and Inequality Constraints
Journal of Mathematical Analysis and Applications 17, 1967, 37-47.
O. L. Mangasarian
Linear and Nonlinear Separation of Patterns by Linear Programming
Operations Research 13, 1965, 444-452.

Courses Taught

CS525: Linear Programming
CS726: Nonlinear Programming Theory
CS730: Nonlinear Programming Algorithms

Support Vector Machine Toolbox

A collection of SVM MATLAB codes based on some of the above papers.

Breast Cancer

Cancer datasets

Chronological cancer bibliography

Internet Links (to Mangasarian)

The Mathematics Genealogy Project, Department of Mathematics, North Dakota State University

University of Trier Database

ACM Portal: The ACM Digital Library

University of Karlsruhe: The Collection of Computer Science Bibliographies

Google Scholar

Media Citations

``Microsoft grant establishes UW Data Mining Institute", Office of News and Public Affairs, University of Wisconsin, June 1, 1999.

Marilynn Marchione: ``Detecting Changes in Breast Cancer Diagnosis", Milwaukee Sentinel, October 10, 1999.

James Case: ``Data Mining Emerges as a New Discipline in a World of Increasingly Massive Data Sets'', SIAM News, Volume 32, Number 10, pages 1 \& 4, December 1999.

``Mangasarian's Pioneering Work in Data Mining Earns Lanchester Prize", ORMS Today, December 2000.

Publications of the Wisconsin MP Group

View and download papers and reports of MP Group

View home page of MP Group.

ftp papers and reports


Contact information:
Email olvi at cs dot wisc dot edu
Telephone 608 262-6593, 608 262-1204
Fax 608 262-9777 . .