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 537061685
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 CCR0138308 and
IIS0511905, 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

PrivacyPreserving 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

PrivacyPreserving Support Vector Machine Classification via Random Kernels
(PowerPoint)
International Symposium on Mathematical Programming 2009.
Chicago August 2328, 2009.
 Olvi Mangasarian & Edward Wild

PrivacyPreserving Support Vector Machines via Random Kernels
(PowerPoint)
DMIN'08 The 4th International Conference on Data Mining
Las Vegas, Nevada July 1417, 2008
DMIN08 Best Academic Research Paper Award.
 Olvi Mangasarian & Edward Wild

PrivacyPreserving 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

KnowledgeBased 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 1013, 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 24, 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 kMedian 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

KnowledgeBased Kernel Approximation
(PowerPoint)
Numerical Analysis Seminar, Mathematics Department,
University of California at San Diego,
January 13, 2004.
 Glenn Fung, Olvi Mangasarian & Jude Shavlik

KnowledgeBased 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 2427, 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 2429, 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

KnowledgeBased Support Vector Machine Classifiers
(PowerPoint)
Neural Information Processing Systems NIPS*2002, Vancouver December 914, 2002.
 G. Fung, O. L. Mangasarian & Alexnader J. Smola

Minimal Kernel Classifiers
(PowerPoint)
INFORMS 2002, San Jose, California, November 1720, 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 1316, 2002.
 O. L. Mangasarian

Support Vector Machines in Data Mining (PowerPoint)
AFOSR Systems & Software Annual Meeting,
Syracuse, NY, June 37, 2002
 G. Fung & O. L. Mangasarian

Incremental Support Vector Machine Classification (PowerPoint)
Second SIAM International Conference on Data Mining SDM 2002
Arlington, Virginia, April 1113, 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 2629, 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 57, 2001. CD ROM Proceedings.
 David R. Musicant & O. L. Mangasarian

LSVM: Lagrangian Support Vector Machines (PowerPoint)
NIPS 2000, Workshop on New Perspectives in KernelBased Learning Methods
Breckenridge, CO, December 1st, 2000
 Glenn Fung & O. L. Mangasarian

Unlabeled Data Classification
INFORMS Annual Meeting, San Antonio, Texas, November 58, 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)
KDD00 Knowledge Discovery and Data Mining, Boston, MA, August 2023, 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 2829, 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 810, 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 710, 1999
 O. L. Mangasarian & D. R. Musicant

Nonlinear Data Discrimination
via Generalized Support Vector Machines
(PowerPoint file here  Philadelphia INFORMS, November 710, 1999)
ICCP99: International Conference on Complementarity Problems, Madison, Wisconsin,
June 912, 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 34, 1999.
 O. L. Mangasarian

Mathematical Programming in Machine Learning
NIPS*98 Workshop on Large Margin Classifiers, Breckenridge, Colorado,
December 45, 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 1601, August 2016. Optimization Letters 11(7) 2017,
14691475.
 G. M. Fung & O. L. Mangasarian

Unsupervised and Semisupervised Classification via Absolute Value Inequalities
Data Mining Institute Technical Report 1403, May 2014. Journal of Optimization Theory and Applications
168(2) 2016, 551558.
 O. L. Mangasarian

A Hybrid Algorithm for Solving the Absolute Value Equation
Data Mining Institute Technical Report 1402, April 2014. Optimization Letters 9(7) 2015, 14691474.
 O. L. Mangasarian

Unsupervised Classification via Convex Absolute Value Inequalities
Data Mining Institute Technical Report 1401, March 2014. Optimization 64(1) 2015, 8186.
 O. L. Mangasarian

Linear Complementarity as Absolute Value Equation Solution
Data Mining Institute Technical Report 1302, March 2013. Optimization Letters 8(4) 2014, 15291534.
 O. L. Mangasarian

Absolute Value Equation Solution via Linear Programming
Data Mining Institute Technical Report 1301, Februaty 2013. Journal of Optimization Theory and
Applications 161, 870876, 2014.
 G. M. Fung and O. L. Mangasarian

PrivacyPreserving Linear and Nonlinear Approximation via Linear Programming
PDF Version
Data Mining Institute Technical Report 1104, October 2011. Optimization Methods and Software 28(1), 207216, 2013.
 O. L. Mangasarian

Absolute Value Equation Solution via Dual Complementarity
PDF Version
Data Mining Institute Technical Report 1103, September 2011. Optimization Letters 7(4), 2013, 625630.
 G. M. Fung and O. L. Mangasarian

Equivalence of Minimal 0Norm and pNorm Solutions of Linear Equalities, Inequalities and
Linear Programs for Sufficiently Small p
PDF Version
Data Mining Institute Technical Report 1102, April 2011. Journal of Optimization Theory and Applications
151, 2011, 110.
 O. L. Mangasarian

PrimalDual Bilinear Programming Solution of the AbsoluteValue Equation
PDF Version
Data Mining Institute Technical Report 1101, February 2011. Optimization Letters 6(7), 15271533, 2012.
 O. L. Mangasarian

PrivacyPreserving HorizontallyPartitioned Linear Programs
PDF Version
Data Mining Institute Technical Report 1002, April 2010. Optimization Letters 6(3), 431436, 2012.
Example of Security Breach Attempt
 O. L. Mangasarian

PrivacyPreserving Linear Programming
PDF Version
Data Mining Institute Technical Report 1001, March 2010. Optimization Letters 5, 165172, 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 0902, September 2009. European Journal of Operations Research 214 (2011) 2730.
 O. L. Mangasarian and M. C. Ferris

Uniqueness of Integer Solution of Linear Equations
PDF Version
Data Mining Institute Technical Report 0901, July 2009. Optimization Letters 4, 559565, 2010.
 O. L. Mangasarian

Knapsack Feasibility as an Absolute Value Equation Solvable by Successive Linear Programming
PDF Version
Data Mining Institute Technical Report 0803, September 2008. Optimization Letters 3(2)
March 2009, 161170.
Online Version
 O. L. Mangasarian and E. W. Wild

PrivacyPreserving Random Kernel Classification of Checkerboard
Partitioned Data
PDF Version
Data Mining Institute Technical Report 0802, September 2008. Annals of Information
Systems XIII, 2010, 375387.
 O. L. Mangasarian

A Generalized Newton Method for Absolute Value Equations
PDF Version
Data Mining Institute Technical Report 0801, May 2008.
Optimization Letters 3(1), January 2009, 101108.
Online Version
 O. L. Mangasarian and E. W. Wild

PrivacyPreserving Classification of Horizontally Partitioned Data
via Random Kernels
PDF Version
Data Mining Institute Technical Report 0703, November 2007.
Proceedings of the 2008 International Conference on Data Mining DMIN08, Las Vegas July 2008, Volume II, 473479,
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

PrivacyPreserving Classification of Vertically Partitioned Data
via Random Kernels
PDF Version
Data Mining Institute Technical Report 0702, 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 0701, July 2007. Optimization, Volume 60, Nos. 12,
JanFeb 2011, 314.
 O. L. Mangasarian and M. E. Thompson

Chunking for Massive Nonlinear Kernel Classification
PDF Version
Data Mining Institute Technical Report 0607, December 2006. Optimization Methods and Software,
23, 2008, 365274.
 O. L. Mangasarian and E. W. Wild

Nonlinear Knowledge in Kernel Machines
PDF Version
Data Mining Institute Technical Report 0606, 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, 181198.
 O. L. Mangasarian, E. W. Wild and G. M. Fung

Proximal KnowledgeBased Classification
PDF Version
Data Mining Institute Technical Report 0605, November 2006.
Statistical Analysis and Data Mining 1(4) 2009, 215222.
 O. L. Mangasarian & E. W. Wild

Nonlinear KnowledgeBased Classification
PDF Version
Data Mining Institute Technical Report 0604, August 2006. IEEE Transactions on Neural Networks
19, October 2008, 18261832.
 O. L. Mangasarian & E. W. Wild

Feature Selection for Nonlinear Kernel Support Vector Machines
PDF Version
Data Mining Institute Technical Report 0603, July 2006.
IEEE Seventh International Conference on Data Mining (ICDM'07)
October 28, 2007, Omaha, NE, Workshop Proceedings 231236.
 O. L. Mangasarian

Absolute Value Equation Solution via Concave Minimization
PDF Version
Data Mining Institute Technical Report 0602, March 2006. Optimization Letters 1(1), 2007, 38.
 O. L. Mangasarian and M. E. Thompson

Massive Data Classification via Unconstrained Support Vector Machines
PDF Version
Data Mining Institute Technical Report 0601, March 2006. Journal of
Optimization Theory and Applications 131(3), December 2006, 315325.
 O. L. Mangasarian and R. R. Meyer

Absolute Value Equations
PDF Version
Data Mining Institute Technical Report 0506, December 2005. Linear
Algebra and Its Applications 419 (2006) 359367.
 O. L. Mangasarian and E. W. Wild

Nonlinear Knowledge in Kernel Approximation
PDF Version
Data Mining Institute Technical Report 0505, October 2005. Revised June 2006.
IEEE Transactions on Neural Networks 18, January 2007, 300306.
 O. L. Mangasarian

Absolute Value Programming
PDF Version
Data Mining Institute Technical Report 0504, September 2005.
Computational Optimization and Applications 36(1), January 2007, 4353.
Computational Optimization and
Applications 2007 Best Paper Award. COAP (2008) 41:147149.
 O. L. Mangasarian

Exact 1Norm Support Vector Machines via Unconstrained
Convex Differentiable Minimization
PDF Version
Data Mining Institute Technical Report 0503, August 2005. Revised January 2006.
Journal of Machine Learning Research 7, 2006, 15171530.
 O. L. Mangasarian and E. W. Wild

Multiple Instance Classification via Successive Linear Programming
PDF Version
Data Mining Institute Technical Report 0502, May 2005. Journal of Optimization Theory and Applications 137(1), 2008, 555568.
 O. L. Mangasarian, J. B. Rosen and M. E. Thompson

Nonconvex PiecewiseQuadratic Underestimation for Global Minimization
PDF Version
Data Mining Institute Technical Report 0501, March 2005, Journal of Global
Optimization 34(4), 2006, 475488.
 O. L. Mangasarian and E. W. Wild

Multisurface Proximal Support Vector Classification via Generalized Eigenvalues
PDF Version
Data Mining Institute Technical Report 0403, June 2004. Revised September 2004.
IEEE Transactions on Pattern Analysis and Machine Intelligence 28(1), 2006, 6974.
"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 0402, May 2004. Computational Optimization
and Applications 34(1), 2006, 3545.
 O. L. Mangasarian and E. W. Wild

Feature Selection in kMedian Clustering
PDF Version
Data Mining Institute Technical Report 0401, 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 2328.
 G. M. Fung and O. L. Mangasarian

Breast Tumor Susceptibility to Chemotherapy via Support Vector Machines
PDF Version
Data Mining Institute Technical Report 0306, November 2003. Computational
Management Science 3, 2006, 103112.
 O. L. Mangasarian, J. W. Shavlik and E. W. Wild

KnowledgeBased Kernel Approximation
PDF Version
Data Mining Institute Technical Report 0305, October 2003. Journal
of Machine Learning Research 5, 11271141, 2004.
 O. L. Mangasarian

KnowledgeBased Linear Programming
PDF Version
Data Mining Institute Technical Report 0304, July 2003.
SIAM Journal on Optimization 15, 2005, 375382.
 O. L. Mangasarian, J. B. Rosen and M. E. Thompson

Global Minimization via PiecewiseLinear Underestimation
PDF Version
Data Mining Institute Technical Report 0303, June 2003. Journal of Global Optimization 32, 2005, 19.
 G. M. Fung, O. L. Mangasarian and J. W. Shavlik

KnowledgeBased Nonlinear Kernel Classifiers
PDF Version
Data Mining Institute Technical Report 0302, 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,
102113.
 O. L. Mangasarian

Support Vector Machine Classification via Parameterless Robust Linear Programming
PDF Version
Data Mining Institute Technical Report 0301, March 2003.
Optimization Methods and Software 20, 2005, 115125.
 Glenn Fung and O. L. Mangasarian

A Feature Selection Newton Method for Support Vector Machine Classification
PDF Version
Data Mining Institute Technical Report 0203, September 2002. Computational
Optimization and Applications 28(2) 185202, 2004.
 O. L. Mangasarian

A Newton Method for Linear Programming
PDF Version
Data Mining Institute Technical Report 0202, March 2002. Revised December 2002. Journal of Optimization Theory and
Applications 121, 2004, 118.
MATLAB Files
 G. Fung and O. L. Mangasarian

Finite Newton Method for Lagrangian Support Vector Machine Classification
PDF Version
Data Mining Institute Technical Report 0201, February 2002.
Neurocomputing 55, September 2003, 3955.
 O. L. Mangasarian

A Finite Newton Method for Classification
PDF Version
Data Mining Institute Technical Report 0111, December 2001. Optimization
Methods and Software 17, 2002, 913929.
 O. L. Mangasarian

Set Containment Characterization
PDF Version
Data Mining Institute Technical Report 0110, November 2001.
Journal of Global Optimization 24(4) December 2002, 473480.
 Glenn Fung, O. L. Mangasarian and Jude Shavlik

KnowledgeBased Support Vector Machine Classifiers
PDF Version
Data Mining Institute Technical Report 0109, November 2001.
Neural Information Processing Systems 2002 (NIPS 2002),
Vancouver, BC, December 1012, 2002. ``Neural Information Processing
Systems 15", S. Becker, S. Thrun and K. Obermayer, editors, MIT Press,
Cambridge, MA, 2003, 521528.
 G. Fung and O. L. Mangasarian

Incremental Support Vector Machine Classification
PDF Version
Data Mining Institute Technical Report 0108, September 2001. Proceedings of
the Second SIAM
International Conference on Data Mining, Arlington, Virginia, April 1113, 2002,R. Grossman, H. Mannila and R. Motwani (editors), SIAM, Philadelphia 2002,
247260.
 G. Fung and O. L. Mangasarian

Multicategory Proximal Support Vector Machine Classifiers
PDF Version
Data Mining Institute Technical Report 0106, July 2001. Machine Learning 59,
2005, 7797.
 O. L. Mangasarian

Data Mining via Support Vector Machines
PDF Version
Data Mining Institute Technical Report 0105, May 2001. IFIP Conference on
System Modelling and Optimization, Trier, Germany, July 2327, 2001.
``System Modeling and Optimization XX", E. W. Sachs and R. Tichatschke,
editors, Kluwer Academic Publishers, Boston 2003, 91112.
 Y.J. Lee, O. L. Mangasarian and W. H. Wolberg

SurvivalTime Classification of Breast Cancer Patients
PDF Version
Data Mining Institute Technical Report 0103, March 2001. Computational
Optimization and Applications 25, 2003, 151166.
 Glenn Fung and O. L. Mangasarian

Proximal Support Vector Machine Classifiers
PDF Version
Data Mining Institute Technical Report 0102, February 2001.
Proceedings KDD2001, San Francisco August 2629, 2001.
Association for Computing Machinery, New York, 2001, 7786.
 Glenn Fung, O. L. Mangasarian & Alexander J. Smola

Minimal Kernel Classifiers
PDF Version
Data Mining Institute Technical Report 0008, November 2000.
Journal of Machine Learning Research 3, 2002, 303321.
http://www.ai.mit.edu/projects/jmlr/
 YuhJye Lee and O. L. Mangasarian

RSVM:
Reduced Support Vector Machines
PDF Version
Data Mining Institute Technical Report 0007, July 2000.
CD Proceedings of the SIAM International
Conference on Data Mining, Chicago, April 57, 2001, SIAM, Philadelphia,
ISBN 0898714958.
 O. L. Mangasarian and David R. Musicant

Lagrangian
Support Vector Machines
PDF Version
Data Mining Institute Technical Report 0006, June 2000.
Journal of Machine Learning Research 1, March 2001, 161177.
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, 577583.
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 0002, February 2000.
"KDD2000", Proceedings of the Sixth ACM SIGKDD International
Conference on Knowledge Discovery and Data Mining, August 2023, 2000, Boston,
MA, R. Ramakrishnan & S. Stolfo, editors, ACM, NY 2000, 6470.
 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 9910, December 1999.
DIMACS Series in Discrete Mathematics and Theoretical Computer Science,
Volume 55, American Mathematical Society 2000, 110.
 O. L. Mangasarian and D. R. Musicant

Robust Linear
and Support Vector Regression
PDF Version
Data Mining Institute Technical Report 9909, November 1999.
IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 2000,
950955.
 Glenn Fung and O. L. Mangasarian

SemiSupervised
Support Vector Machines for Unlabeled Data Classification.
PDF Version
Data Mining Institute Technical Report 9905, October 1999. Optimization
Methods and Software 15, 2001, 2944.
 Alex J. Smola, Olvi L. Mangasarian and Bernhard Schoelkopf

Sparse Kernel
Feature Analysis.
Data Mining Institute Technical Report 9904, October 1999. 24th Annual
Conference of Gesellschaft für Klassifikation, University of Passau,
Passau, Germany March 1517, 2000.
 Y.J. Lee and O. L. Mangasarian

SSVM: A Smooth
Support Vector Machine for Classification
PDF Version
Data Mining Institute Technical Report 9903, September 1999,
Computational Optimization and Applications 20(1), October 2001, 522.
 O. L. Mangasarian and David R. Musicant

Large Scale
Kernel Regression via Linear Programming
PDF Version
Data Mining Institute Technical Report 9902, August 1999, Machine Learning
46(1/3), 255269, January 2002.
 P. S. Bradley, O. L. Mangasarian and David R. Musicant

Optimization
Methods in Massive Datasets.
Data Mining Technical Report 9901, June 1999. "Handbook of Massive Datasets", J. Abello , P. M. Pardalos,
M. G. C. Resende, editors, Kluwer Academic Publishers, 2002, 439472.
 O. L. Mangasarian and David R. Musicant

Data Discrimination via Nonlinear Generalized Support Vector Machines
Mathematical Programming Technical Report 9903, March 1999.
"Complementarity: Applications, Algorithms and Extensions", in
M. C. Ferris, O. L. Mangasarian and J.S. Pang, editors, Kluwer Academic
Publishers, 2001, 233251.
 O. L. Mangasarian and David R. Musicant

Successive Overrelaxation for Support Vector Machines.
Mathematical Programming Technical Report 9818, November 1998. IEEE Transactions on Neural Networks, 10,
September 1999, 10321037.
 O. L. Mangasarian

Generalized Support Vector Machines (Technical Report Version)
PDF Version
(MIT Press Version)
Mathematical Programming Technical Report 9814, October 1998. "Advances in
Large Margin
Classifiers", A. J. Smola, P. Bartlett, B. Sch\"{o}kopf and D. Schuurmans,
editors, MIT Press, 2000, 135146.
 P. S. Bradley & O. L. Mangasarian

kPlane Clustering.
Mathematical Programming Technical Report 9808, August 1998. Journal of
Global Optimization 16, Number 1, 2000, 2332.
 P. S. Bradley & O. L. Mangasarian

Massive Data Discrimination via Linear Support Vector Machines.
Mathematical Programming Technical Report 9805, May 1998. Revised
March 31, 1999. Optimization Methods and Software, 13(1), 2000, 110.
 P. S. Bradley & O. L. Mangasarian

Feature Selection via Concave Minimization and Support Vector Machines.
Mathematical Programming Technical Report 9803, February 1998.
"Machine Learning Proceedings of the Fifteenth International
Conference(ICML '98)", J. Shavlik, editor, Morgan Kaufmann, San Francisco,
California, 8290, 1998.
 P. S. Bradley, Usama M. Fayyad & O. L. Mangasarian

Mathematical Programming for Data Mining: Formulations and Challenges.
PDF Version
Mathematical Programming Technical Report 9801, January 1998. Revised July 1998
.
INFORMS Journal on Computing 11, 1999, 217238.
 O. L. Mangasarian

Regularized Linear Programs with Equilibrium Constraints.
Mathematical Programming Technical Report 9713, November 1997.
In "ReformulationNonsmooth, Piecewise Smooth,
Semismooth and Smoothing Methods", M. Fukushima and Liqun Qi, editors,
Kluwer Academic Publishers, 1998, 259268.
 P. S. Bradley & O. L. Mangasarian

Parsimonious Side Propagation,
Mathematical Programming Technical Report 9711, October 1997.
In "ICASSP98: IEEE International Conference on Acoustics, Speech
and Signal Processing, Seattle May 1215, 1998, Volume 3,
pages 18731876.
 O. L. Mangasarian

Polyhedral Boundary Projection.
Mathematical Programming Technical Report 9710, October 1997, SIAM
Journal on Optimization 9, 1999, 11281134.
 O. L. Mangasarian

ArbitraryNorm Separating Plane.
Mathematical Programming Technical Report 9707, May 1997.
 O. L. Mangasarian

ArbitraryNorm Separating Plane.
Mathematical Programming Technical Report 9707r, May 1997,
Revised September 1998. Operations Research Letters 24, 1999, 1523.
 O. L. Mangasarian

MinimumSupport Solutions of Polyhedral Concave Programs
Mathematical Programming Technical Report 9705, April 1997. Revised March 1998,
Optimization 45, 1999, 149162.
 P. S. Bradley, O. L. Mangasarian and J. B. Rosen

Parsimonious Least Norm Approximation
Mathematical Programming Technical Report 9703, March 1997.
Computational Optimization and Applications 11(1), October 1998, 521.
 O. L. Mangasarian

Solution of General Linear Complementarity Problems via
Nondifferentiable Concave Minimization.
Mathematical Programming Technical Report 9610, November 1996,
Acta Mathematica Vietnamica, 22(1), 1997, 199205.
 O. L. Mangasarian and M. V. Solodov

A Linearly Convergent DerivativeFree Descent Method for Strongly Monotone
Complementarity Problems.
Mathematical Programming Technical Report 9607, October 1996,
Computational Optimization & Applications 14, 1999, 516.
 O. L. Mangasarian and JongShi Pang

Exact Penalty Functions for Mathematical Programs
with Linear Complementarity Constraints.
Mathematical Programming Technical Report 9606, August 1996, Optimization
42(1), 1997, 18.
 O. L. Mangasarian

Mathematical Programming in Data Mining
Mathematical Programming Technical Report 9605, August 1996 
Revised November 1996 and March 1997, Data Mining and Knowledge Discovery,
1(2), 1997, 183201.
 O. L. Mangasarian

Error Bounds for Nondifferentiable Convex Inequalities under a Strong
Slater Constraint Qualification.
Mathematical Programming Technical Report 9604, July 1996. Revised March 1997, Mathematical Programming, 83, 1998, 187194.
 P. S. Bradley, O. L. Mangasarian and W. N. Street

Clustering via Concave Minimization.
Mathematical Programming Technical Report 9603, May 1996.
Advances in Neural Information Processing Systems 9, MIT Press,
Cambridge, MA 1997, 368374.
 W. N. Street, O. L. Mangasarian and W. H. Wolberg

Individual and Collective Prognostic Prediction.
Mathematical Programming Technical Report 9601, January 1996.
 P. S. Bradley, O. L. Mangasarian and W. N. Street

Feature Selection via Mathematical Programming.
Mathematical Programming Technical Report 9521, December 1995.
INFORMS Journal on Computing 10, 1998, 209217.
 O. L. Mangasarian

Machine Learning via Polyhedral Concave Minimization.
Mathematical Programming Technical Report 9520, November 1995.
"Applied Mathematics and Parallel Computing  Festschrift for
Klaus Ritter", H. Fischer, B. Riedmueller, S. Schaeffler, editors,
PhysicaVerlag, Germany 1996, 175188.
 O. L. Mangasarian

The IllPosed Linear Complementarity Problem.
Mathematical Programming Technical Report 9515, August 1995, Revised
November 1995. "Complementarity and Variational Problems", M. C. Ferris
and J.S. Pang, editors, SIAM, Philadelphia, PA, 1997, 226233.
 W. Nick Street and O. L. Mangasarian

Improved Generalization via Tolerant Training.
Mathematical Programming Technical Report 9511, July 1995. Journal of
Optimization Theory and Applications, 96(2), February 1998, 259279.
 O. L. Mangasarian

Mathematical Programming in Machine Learning.
Mathematical Programming Technical Report 9506, 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,
283295.
 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, 522530, 1995.
 Chunhui Chen and O. L. Mangasarian

Hybrid Misclassification Minimization.
Mathematical Programming Technical Report 9505, February 1995,
Revised July 1995 and August 1995.
Advances in Computational Mathematics 5(2) 1996, 127136.
 O. L. Mangasarian

Optimization in Machine Learning.
Mathematical Programming Technical Report 9501, January 1995.
SIAG/OPT ViewsandNews 6, 1995, 37.
 W. H. Wolberg, W. N. Street and O. L. Mangasarian

Computerized breast cancer diagnosis from fine needle aspirates.
Archives of Surgery 130, 511516, 1995.
 Chunhui Chen and O. L. Mangasarian

A Class of Smoothing Functions for Nonlinear and Mixed Complementarity Problems.
Mathematical Programming Technical Report 9411, August 1994.
Revised October 1994, February 1995 and September 1995.
Computational Optimization and Applications 5, 1996, 97138.
 O. L. Mangasarian, W. Nick Street and W. H. Wolberg

Breast Cancer Diagnosis and Prognosis via Linear Programming.
Mathematical Programming Technical Report 9410, August 1994.
Revised December 1994.
Operations Research 43(4), JulyAugust 1995, 570577.
 O. L. Mangasarian

The Linear Complementarity Problem as a Separable Bilinear Program.
Mathematical Programming Technical Report 9409, July 1994.
Journal of Global Optimization 6, 1995, 153161.
 O. L. Mangasarian and M. V. Solodov

Backpropagation Convergence via Deterministic Nonmonotone Perturbed Minimization.
Mathematical Programming Technical Report 9406, June 1994.
Advances in Neural Information Processing Systems 6,
(J. D. Cowan, G. Tesauro and J. Alspector, editors) 383390,
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, 5169.
 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, 359368.
 O. L. Mangasarian

Misclassification Minimization.
Computer Sciences Technical Report 1186, October 1993.
Revised September 1994.
Journal of Global Optimization 5(4), December 1994, 309323.
 O. L. Mangasarian

Error Bounds for Inconsistent Linear Inequalities and Programs.
Computer Sciences Technical Report 1166, July 1993.
Operations Research Letters 15, May 1994, 187192.
 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, 103116.
 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, 19161925.
 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 861870, San Jose, California, 1993.
 O. L. Mangasarian

Mathematical Programming in Neural Networks.
Computer Sciences Technical Report 1129, 1992. ORSA Journal on
Computing 5, 1993, 349360.
 K. P. Bennett and O. L. Mangasarian

Multicategory Discrimination via Linear Programming.
Computer Sciences Technical Report 1127, 1992. Optimization Methods and Software
3, 1994, 2739.
 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, 396404
 K. P. Bennett and O. L. Mangasarian

Bilinear Separation of Two Sets in nSpace.
Computer Sciences Technical Report 1109, 1992. Computational
Optimization and Applications 2, 1993, 207227.
 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, 277297.
 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, 293305.
 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, 2334.
 Michael C. Ferris and O. L. Mangasarian

Parallel Constraint Distribution.
Computer Sciences Technical Report 971, 1990.
SIAM Journal on Optimization 1, 1991, 487500.
 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."LargeScale Numerical Optimization
", T. F. Coleman and Y. Li, editors, SIAM, Philadelphia, Pennsylvania 1990, 223
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, 2126.
 O. L. Mangasarian and T.H. Shiau

Variable Complexity Norm Maximization Problem
SIAM Journal on Algebraic and Discrete Methods 7(3), 1986, 455461.
 O. L. Mangasarian and R. R. Meyer

Nonlinear Perturbation of Linear Programs
SIAM Journal on Control and Optimization 17(6), 1979, 745752.
 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, 3747.
 O. L. Mangasarian

Linear and Nonlinear Separation of Patterns by Linear Programming
Operations Research 13, 1965, 444452.
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 2626593, 608 2621204
Fax 608 2629777
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