Dave Musicant

Publications:

David Musicant, Abha Laddha, Tom Choi: Open-Ended Robotics Exploration Projects for Budding Researchers; Proceedings of the 2017 AAAI Conference on Artificial Intelligence.

Shilad W. Sen, Heather Ford, David R. Musicant, Mark Graham, Oliver S.B. Keyes, Brent Hecht: Barriers to the Localness of Volunteered Geographic Information; Proceedings of the 2015 SIGCHI Conference on Human Factors in Computing Systems, CHI 2015.

David R. Musicant and S. Selcen Guzey: Engaging High School Students in Modeling and Simulation through Educational Media; Association for Computing Machinery Special Interest Group in Computer Science Education Technical Symposium (ACM SIGCSE), Kansas City, MO, March 6, 2015.

Heather Ford, David R. Musicant, Shilad Sen, Nathaniel Miller: Getting to the Source: Where Does Wikipedia Get Its Information From?; WikiSym '13: Proceedings of the 9th International Symposium on Wikis and Open Collaboration, 2013.

Rachel Adams, Alex Kuntz, Morgan Marks, William Martin, David R. Musicant: Keeping Wiki Content Current via News Sources; IUI '13 Companion: Proceedings of the Companion Publication of the 2013 International Conference on Intelligent User Interfaces, 2013, pp. 51-52.

Laurie Smith King, David R. Musicant, Tracy Camp, Paul Tymann, Brad Miller (Editors): SIGCSE '12: Proceedings of the 43rd ACM Technical Symposium on Computer Science Education.; February 29-March 3, 2012. Association for Computing Machinery, 2012.

David R. Musicant, Yuqing Ren, James A. Johnson, John Riedl: Mentoring in Wikipedia: A Clash of Cultures; WikiSym '11: Proceedings of the 7th International Symposium on Wikis and Open Collaboration, 2011, pp. 173-182.

Shyong (Tony) K. Lam, Anuradha Uduwage, Zhenhua Dong, Shilad Sen, David R. Musicant, Loren Terveen, John Riedl: WP:Clubhouse? An Exploration of Wikipedia's Gender Imbalance; WikiSym '11: Proceedings of the 7th International Symposium on Wikis and Open Collaboration, 2011, pp. 1-10.

Thomas J. Cortina, Ellen L. Walker, Laruie Smith King, David R. Musicant, Lester McCann (Editors): SIGCSE '11: Proceedings of the 42nd ACM Technical Symposium on Computer Science Education.; March 9-12, 2011. Association for Computing Machinery, 2011.

Gary Lewandowski, Steven Wolfman, Thomas J. Cortina, Ellen L. Walker, David R. Musicant (Editors): SIGCSE '10: Proceedings of the 41st ACM Technical Symposium on Computer Science Education.; March 10-13, 2010. Association for Computing Machinery, 2010.

Deborah S. Gross, Robert Atlas, Jeffrey Rzeszotarski, Emma Turetsky, Janara Christensen, Sami Benzaid, Jamie Olson, Thomas Smith, Leah Steinberg, Jon Sulman, Anna Ritz, Benjamin Anderson, Catherine Nelson, David R. Musicant, Lei Chen, David C. Snyder, James J. Schauer: Environmental Chemistry through Intelligent Atmospheric Data Analysis; Environmental Modeling and Software, 25:6, pp. 760-769, June 2010.

David R. Musicant, Robert Atlas, Janara M. Christensen, Jamie F. Olson, Jeffrey M. Rzeszotarski, Emma R. D. Turetsky: Supervised Learning by Training on Aggregate Outputs; Expanded version of below conference paper. Carleton College Computer Science Technical report 2009drm1.

David Barbella, Sami Benzaid, Janara Christensen, Bret Jackson, Victor Qin, David Musicant: Understanding Support Vector Machine Classifications: A Local Approach; Proceedings of The International Conference on Data Mining (DMIN '09), Editors: Robert Stahlbock, Sven F. Crone, and Stefan Lessmann. CSREA Press, 2009, pages 305-311.

David R. Musicant, Janara M. Christensen, Jamie F. Olson: Supervised Learning by Training on Aggregate Outputs; Proceedings of the Seventh IEEE International Conference on Data Mining, IEEE Press, 2007, pages 252-261.; Copyright (C) 2007 IEEE.

Amy Csizmar Dalal, David R. Musicant, Jamie Olson, Brandy McMenamy, Sami Benzaid, Ben Kazez, Erica Bolan: Predicting User-Perceived Quality Ratings from Streaming Media Data; Proceedings of the 2007 IEEE International Conference on Communications (ICC-2007), IEEE Press, 2007, pp. 65-72.

David R. Musicant: A Data Mining Course for Computer Science: Primary Sources and Implementations; Proceedings of the 2006 ACM SIGCSE Conference, Houston TX, pages 538-542.; Copyright ACM, 2006. This is the author's version of the work. It was posted here by permission of ACM for your personal use. Not for redistribution. The definitive version will be posted as cited above.

Benjamin J. Anderson, Deborah S. Gross, David R. Musicant, Anna M. Ritz, Thomas G. Smith, Leah E. Steinberg: Adapting K-Medians to Generate Normalized Cluster Centers; Proceedings of the Sixth SIAM International Conference on Data Mining, Joydeep Ghosh, Diane Lambert, David Skillcorn, Jaideep Srivastava, editors, Society for Industrial and Applied Mathematics, Bethesda, MD, 2006, pages 165-175.

Benjamin J. Anderson, David R. Musicant, Anna M. Ritz, Andrew Ault, Deborah S. Gross, Melanie Yuen, Markus Gaelli: User-Friendly Clustering for Atmospheric Data Analysis; Carleton College Computer Science Technical Report 2005a.

Bee-Chung Chen, Lei Chen, Raghu Ramakrishnan, D.R. Musicant: Learning from Aggregate Views; Proceedings of the 22nd International Conference on Data Engineering, Ling Liu, Andreas Reuter, Kyu-Young Whang, Jianjun Zhang, editors, Atlanta, GA, 2006, page 3.

David R. Musicant: Support Vector Machines Illuminated; Encyclopedia of Data Warehousing and Mining, July 2005, pages 1071-1076.

R. Ramakrishnan, J. J. Schauer, L. Chen, Z. Huang, M. Shafer, D. S. Gross, David R. Musicant: The EDAM Project: Mining Atmospheric Aerosol Datasets; International Journal of Intelligent Systems, July 2005 (Volume 20 Issue 7), pages 759-787.

David R. Musicant and Jeff Ondich: A Model for a Liberal Arts Project-Based Capstone Experience; (ps)(pdf); Carleton College Computer Science Technical Report 2004a, September 2004.

Z. Huang, L. Chen, J.-Y. Cai, D.S. Gross, David R. Musicant, R. Ramakrishnan, J. J. Schauer, S. J. Wright: Mass Spectrum Labeling: Theory and Practice; Proceedings of the Fourth IEEE International Conference on Data Mining, IEEE Press, 2004, pages 122-129.; 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.

David R. Musicant and Alexander Feinberg: Active Set Support Vector Regression; (ps)(pdf); IEEE Transactions on Neural Networks 15, March 2004, 268-275.; 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.

David R. Musicant, V. Kumar, and A. Ozgur: Optimizing F-Measure with Support Vector Machines; Proceedings of the Sixteenth International Florida Artificial Intelligence Research Society Conference, I. Russell and S. Haller, editors, AAAI Press 2003, 356-360.

Sebastian Celis and David R. Musicant: Weka-Parallel: Machine Learning in Parallel; Carleton College Computer Science Technical Report 2002b, August 2002.

O. L. Mangasarian and David R. Musicant: Large Scale Kernel Regression via Linear Programming; Machine Learning 46, January 2002, 255-269.

P. S. Bradley, O. L. Mangasarian and David R. Musicant: Optimization Methods in Massive Datasets; "Handbook of Massive Datasets", J. Abello , P. M. Pardalos, M. G. C. Resende, editors, Kluwer Academic Publishers 2002, 439-472.

Brad Davis, Ethan Sommer, and David R. Musicant: NCV: A Machine Learning Environment for Parallel Evaluation; Carleton College Computer Science Technical Report 2001-01, August 2001.

O. L. Mangasarian and David. R. Musicant: Lagrangian Support Vector Machines; (ps)(pdf)(html); Journal of Machine Learning Research 1, March 2001, 161-177.

O. L. Mangasarian and David. R. Musicant: Active Set Support Vector Machine Classification; Advances in Neural Information Processing Systems 13, Todd K. Leen, Thomas G. Dietterich, and Volker Tresp, editors. MIT Press, Cambridge, MA, 2001, pages 577-583.

O. L. Mangasarian and David R. Musicant: Data Discrimination via Nonlinear Generalized Support Vector Machines; Complementarity: Applications, Algorithms and Extensions, M. C. Ferris, O. L. Mangasarian and J.-S. Pang, editors, Kluwer Academic Publishers, Dordrecht, The Netherlands, 2001, pages 233-251.

O. L. Mangasarian and D. R. Musicant: Robust Linear and Support Vector Regression; IEEE Transactions on Pattern Analysis and Machine Intelligence 22, September 2000, 950-955.; 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.

D. R. Musicant: Data Mining via Mathematical Programming and Machine Learning; Ph.D. Thesis, University of Wisconsin - Madison, July, 2000.

O. L. Mangasarian and David R. Musicant: Successive Overrelaxation for Support Vector Machines.; IEEE Transactions on Neural Networks, 10, 1999, 1032-1037.; 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.