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IEEE Intelligent Systems. 01/2010; 25:86-91.
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IEEE T. Geoscience and Remote Sensing. 01/2010; 48:4023-4033.
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Mach. Vis. Appl. 01/2008; 19:467-482.
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2007 IEEE International Conference on Robotics and Automation, ICRA 2007, 10-14 April 2007, Roma, Italy; 01/2007
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Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Jose, California, USA, August 12-15, 2007; 01/2007
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J. Field Robotics. 01/2007; 24:379-397.
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[show abstract]
[hide abstract]
ABSTRACT: We are developing a model-driven sensor web in order to enable science-driven asset command and control. This not only will optimize resource use, but will also result in a more rapid response to alerts of volcanic eruptions.
NASA SCIENCE TECHNOLOGY CONFERENCE. 01/2007;
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Proceedings of the International Conference on Image Processing, ICIP 2006, October 8-11, Atlanta, Georgia, USA; 01/2006
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Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, August 20-23, 2006; 01/2006
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Steve A. Chien,
Benjamin Cichy,
Ashley Davies,
Daniel Tran,
Gregg Rabideau, Rebecca Castaño,
Rob Sherwood,
Dan Mandl,
Stuart Frye,
Seth Shulman,
Jeremy Jones,
Sandy Grosvenor
IEEE Intelligent Systems. 01/2005; 20:16-24.
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4th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2005), July 25-29, 2005, Utrecht, The Netherlands; 01/2005
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4th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2005), July 25-29, 2005, Utrecht, The Netherlands; 01/2005
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Steve A. Chien,
Rob Sherwood,
Daniel Tran,
Benjamin Cichy,
Gregg Rabideau, Rebecca Castaño,
Ashley Davies,
Dan Mandl,
Stuart Frye,
Bruce Trout,
Jeff D'Agostino,
Seth Shulman,
Darrell Boyer,
Sandra C. Hayden,
Adam Sweet,
Scott Christa
4rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2005), July 25-29, 2005, Utrecht, The Netherlands - Special Track for Industrial Applications; 01/2005
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AI 2004: Advances in Artificial Intelligence, 17th Australian Joint Conference on Artificial Intelligence, Cairns, Australia, December 4-6, 2004, Proceedings; 01/2004
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AI 2002: Advances in Artificial Intelligence, 15th Australian Joint Conference on Artificial Intelligence, Canberra, Australia, December 2-6, 2002, Proceedings; 01/2002
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Steve A. Chien,
Rob Sherwood,
Gregg Rabideau, Rebecca Castaño,
Ashley Davies,
Michael C. Burl,
Russell Knight,
Timothy M. Stough,
Joseph Roden,
Paul Zetocha,
Ross Wainwright,
Pete Klupar,
Jim Van Gaasbeck,
Pat Cappelaere,
Dean Oswald
The First International Joint Conference on Autonomous Agents & Multiagent Systems, AAMAS 2002, July 15-19, 2002, Bologna, Italy, Proceedings; 01/2002
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Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference, May 21-23, 2001, Key West, Florida, USA; 01/2001
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Proceedings of the Sixteenth National Conference on Artificial Intelligence and Eleventh Conference on Innovative Applications of Artificial Intelligence, July 18-22, 1999, Orlando, Florida, USA.; 01/1999
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Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29 - December 4, 1999]; 01/1999
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[show abstract]
[hide abstract]
ABSTRACT: We introduce a general type of optimization algorithm which infers data models relating two different but intertwined types of information about each of a set of objects. A novel clustering problem is solved by formulating an objective function which is optimized. For the optimization of an objective function describing a general classification problem we use a clocked objective function update scheme. As a concrete example we apply the clustering algorithm to geological data (rocks) to infer the spatial as well as mineral relationships within a field geology model. We test the algorithm with synthetic data generated according to a particularly chosen probability distribution function.
