5 Result(s)
within
Kiri L. Wagstaff
English
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Article
Open AccessComparison of novelty detection methods for multispectral images in rover-based planetary exploration missions
Science teams for rover-based planetary exploration missions like the Mars Science Laboratory Curiosity rover have limited time for analyzing new data before making decisions about follow-up observations. Ther...
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Article
Machine learning for science and society
The special issue on “Machine Learning for Science and Society” showcases machine learning work with influence on our current and future society. These papers address several key problems such as how we perfor...
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Article
Machine learning in space: extending our reach
We introduce the challenge of using machine learning effectively in space applications and motivate the domain for future researchers. Machine learning can be used to enable greater autonomy to improve the dur...
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Chapter and Conference Paper
Active Learning with Irrelevant Examples
Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there may exist unlabeled items that are irrele...
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Chapter and Conference Paper
Measuring Constraint-Set Utility for Partitional Clustering Algorithms
Clustering with constraints is an active area of machine learning and data mining research. Previous empirical work has convincingly shown that adding constraints to clustering improves performance, with respe...
