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Lukas Mandrake, Kiri L. Wagstaff, Damhnait Gleeson, Umaa Rebbapragada, Daniel Tran, Rebecca Castano, Steven Chien, Robert T. Pappalardo.
Onboard SVM Analysis of Hyperion Data to Detect Sulfur Deposits in Arctic Regions.
Proceedings of the IEEE WHISPERS conference, August 2009.
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(CL #09-1964)
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Robert Granat, Kiri L. Wagstaff, Benjamin Bornstein, Benyang Tang, and Michael Turmon.
Simulating and Detecting Radiation-Induced Errors for Onboard Machine Learning.
Proceedings of the Third IEEE International Conference on Space Mission Challenges for Information Technology (SMC-IT), July 2009.
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(CL #09-1474)
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Lukas Mandrake, Kiri L. Wagstaff, Damhnait Gleeson, Umaa Rebbapragada, Daniel Tran, Rebecca Castano, Steven Chien, Robert T. Pappalardo.
Hyperspectral Sulfur Detection Using an SVM with Extreme Minority Positive Examples Onboard EO-1.
IJCAI AI in Space Workshop Conference Presentation, July 2009.
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(CL #09-2372)
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Kiri L. Wagstaff and Benjamin Bornstein.
How much Memory Radiation Protection do Onboard Machine Learning Algorithms Require?.
Proceedings of the IJCAI-09/SMC-IT-09/IWPSS-09 Workshop on Artificial Intelligence in Space, July 2009.
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(CL #09-2771)
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Kiri L. Wagstaff and Benjamin Bornstein.
K-means in Space: A Radiation Sensitivity Evaluation.
Proceedings of the Twenty-Sixth International Conference on Machine Learning (ICML), June 2009.
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(CL #09-1355)
[Note: An error in units conversion causes the experiments in this paper to over-estimate the impact of radiation. See 'How much Memory Radiation Protection do Onboard Machine Learning Algorithms Require?' above for updated results.]
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Lukas Mandrake, Kiri L. Wagstaff, Damhnait Gleeson, Umaa Rebbapragada, Daniel Tran, Rebecca Castano, Steven Chien, Robert T. Pappalardo.
Onboard Detection of Natural Sulfur on a Glacier via an SVM and Hyperion Data.
Proceedings of the 30th IEEE Aerospace Conference, March 2009.
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(CL #08-4689)
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Umaa Rebbapragada, Lukas Mandrake, Kiri L. Wagstaff, Damhnait Gleeson, Rebecca Castano, Steve Chien, and Carla E. Brodley.
Improving Onboard Analysis of Hyperion Images by Filtering Mislabeled Training Data Examples.
Proceedings of the 30th IEEE Aerospace Conference, March 2009.
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(CL #09-0103)
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Kiri L. Wagstaff, Terran Lane, and Alex Roper.
Multiple-Instance Regression with Structured Data.
Proceedings of the 4th International Workshop on Mining Complex Data, December 2008.
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(CL #08-3940)
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Kiri L. Wagstaff, Ken Peters, and Lucas Scharenbroich.
From Protocol Specification to Statechart to Implementation.
JPL Technical Report, 2008.
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(CL #08-4014)
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Rebecca Castano, Kiri Wagstaff, Damhnait Gleeson, Robert Pappalardo, Steve Chien, Daniel Tran, Lucas Scharenbroich, Baback Moghaddam, Benyang Tang, Brian Bue, Thomas Doggett, Dan Mandl, and Stuart Frye.
Onboard Detection of Active Canadian Sulfur Springs: A Europa Analogue.
Proceedings of the 9th International Symposium on Artificial Intelligence, Robotics, and Automation in Space, February 2008.
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(CL #07-4419)
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Kiri L. Wagstaff, Edward Benowitz, DJ Byrne, Ken Peters, and Garth Watney.
Automatic Code Generation for Instrument Flight Software.
Proceedings of the 9th International Symposium on Artificial Intelligence, Robotics, and Automation in Space, February 2008.
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(CL #07-4374)
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Kiri L. Wagstaff, Timothy N. Titus, Anton B. Ivanov, and Rebecca Castano.
Observations of the North Polar Water Ice Annulus on Mars using THEMIS and TES.
Planetary and Space Science, 56:2, p. 256-265, January 2008.
Abstract/PDF (ScienceDirect)
(CL #07-1701)
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Kiri L. Wagstaff.
Value, Cost, and Sharing: Open Issues in Constrained Clustering.
Knowledge Discovery in Inductive Databases (KDID 2006), LNCS 4747, p. 1-10, 2007.
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(CL #06-2844)
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Rebecca Castano, Kiri L. Wagstaff, Steve Chien, Timothy M. Stough, and Benyang Tang.
On-board Analysis of Uncalibrated Data for a Spacecraft at Mars.
Proceedings of the Thirteenth International Conference on Knowledge Discovery and Data Mining (KDD), p. 922-930, August 2007.
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(CL #07-0899)
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Kiri L. Wagstaff and Terran Lane.
Salience Assignment for Multiple-Instance Regression.
ICML 2007 Workshop on Constrained Optimization and Structured Output Spaces, July 2007.
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(CL #07-1809)
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Dominic Mazzoni, Kiri L. Wagstaff, and Michael Burl.
Active Learning with Irrelevant Examples.
Proceedings of the Seventeenth European Conference on Machine Learning, September 2006.
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(CL #06-1838)
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Ian Davidson, Kiri L. Wagstaff, and Sugato Basu.
Measuring Constraint-Set Utility for Partitional Clustering Algorithms.
Proceedings of the Tenth European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), September 2006.
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(CL #06-1843)
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Kiri L. Wagstaff, Sugato Basu, and Ian Davidson.
When is Constrained Clustering Beneficial, and Why?.
Proceedings of the Twenty-First National Conference on Artificial Intelligence (Member Abstracts), July 2006.
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(CL #06-1417)
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Marie desJardins, Eric Eaton, and Kiri L. Wagstaff.
Learning User Preferences for Sets of Objects.
Proceedings of the Twenty-Third International Conference on Machine Learning, June 2006.
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(CL #06-1230)
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Kiri Wagstaff and Dominic Mazzoni.
Recent HARVIST Results: Classifying Crops from Remote Sensing Data.
Proceedings of the Second NASA Data Mining Workshop, May 2006.
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(CL #06-2015)
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Kiri L. Wagstaff, Joshua L. Bandfield, Rebecca Castano, Steve Chien, and Michael D. Smith.
Dust Storms and Water Ice Clouds: Feature Detection for Use Onboard THEMIS.
37th Lunar and Planetary Science Conference, March 2006.
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(CL #06-0570)
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Kiri L. Wagstaff, Henry P. Shu, Dominic Mazzoni, and Rebecca Castano.
Semi-Supervised Data Summarization: Using Spectral Libraries to Improve Hyperspectral Clustering.
The Interplanetary Network Progress Report, vol. 42-163, November 2005.
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(CL #05-3746)
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Jon Vandegriff, Kiri Wagstaff, George Ho, and Janice Plauger.
Forecasting Space Weather: Predicting Interplanetary Shocks Using Neural Networks.
Advances in Space Research, vol. 36, p. 2323-2327, November 2005.
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Qianjun Xu, Marie desJardins, and Kiri L. Wagstaff.
Active Constrained Clustering by Examining Spectral Eigenvectors.
Proceedings of the Eighth International Conference on Discovery Science, October 2005.
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(CL #05-2276)
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Kiri L. Wagstaff, Rebecca Castano, Steve Chien, Anton B. Ivanov, and Timothy N. Titus.
An Onboard Data Analysis Method to Track the Seasonal Polar Caps on Mars.
Proceedings of the International Symposium on Artificial Intelligence, Robotics, and Automation in Space, September 2005.
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(CL #05-1883)
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Marie desJardins and Kiri L. Wagstaff.
DD-PREF: A Language for Expressing Preferences Over Sets.
Proceedings of the Twentieth National Conference on Artificial Intelligence, p. 620-626, July 2005.
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(CL #05-1360)
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Kiri L. Wagstaff, Dominic Mazzoni, and Stephan Sain.
HARVIST: A System for Agricultural and Weather Studies Using Advanced Statistical Models.
Proceedings of the Earth-Sun Systems Technology Conference, June 2005.
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(CL #05-1370)
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Qianjun Xu, Marie desJardins, and Kiri Wagstaff.
Constrained Spectral Clustering under a Local Proximity Structure.
Proceedings of the 18th International Florida Artificial Intelligence Research Society (FLAIRS) Conference, May 2005.
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(CL #05-1165)
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Marie desJardins, Eric Eaton, and Kiri Wagstaff.
A Context-Sensitive and User-Centric Approach to Developing Personal Assistants.
Persistent Assistants: Living and Working with AI (AAAI Spring Symposium), April 2005.
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Rebecca Castano, Michele Judd, Tara Estlin, Robert C. Anderson, Daniel Gaines, Andres Castano, Ben Bornstein, Tim Stough, and Kiri Wagstaff.
Current Results from a Rover Science Data Analysis System.
Proceedings of the 2005 IEEE Aerospace Conference, March 2005.
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(CL #05-0185)
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Kiri L. Wagstaff, Rebecca Castano, Steve Chien, Anton B. Ivanov, and Timothy N. Titus.
Towards Onboard Orbital Tracking of Seasonal Polar Volatiles on Mars.
36th Lunar and Planetary Science Conference, March 2005.
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(CL #05-0658)
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Rebecca Castano, Kiri Wagstaff, Lin Song, and Robert C. Anderson.
Validating Rover Image Prioritizations.
The Interplanetary Network Progress Report, vol. 42-160, February 2005.
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(CL #05-0810)
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Kiri L. Wagstaff and Victoria G. Laidler.
Making the Most of Missing Values: Object Clustering with Partial Data in Astronomy.
Astronomical Data Analysis Software and Systems XIV (ADASS), ASP Conference Series, 2005.
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(CL #04-3794)
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Dominic Mazzoni, Kiri Wagstaff, and Rebecca Castano.
Using Trained Pixel Classifiers to Select Images of Interest.
The Interplanetary Network Progress Report, vol. 42-158, 2004.
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Kiri Wagstaff.
Clustering with Missing Values: No Imputation Required.
Classification, Clustering, and Data Mining Applications (Proceedings of the Meeting of the International Federation of Classification Societies), p. 649-658, 2004.
(CL #04-2269)
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Stefan Schroedl, Kiri Wagstaff, Seth Rogers, Pat Langley, and Christopher Wilson.
Mining GPS Traces for Map Refinement.
Data Mining and Knowledge Discovery, vol. 9, issue 1, p. 59-87, 2004.
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K. Wagstaff, R. Castano, S. Dolinar, M. Klimesh, R. Mukai.
Science-based Region-of-Interest Image Compression.
Lunar and Planetary Science Conference (LPSC), March 2004.
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(CL #04-0107)
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