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Accelerating Exact k-means Algorithms with Geometric Reasoning

Document Type: Paper
Tags: Statistical Data Mining for Astrophysics, Cached Sufficient Statistics, Astrostatistics, Clustering, Efficient Statistical Algorithms, Kd-trees and Ball-trees, Mixture Models

A K-means tutorial. We present new algorithms for the k-means clustering problem. They use the kd-tree data structure to reduce the large number of nearest-neighbor queries issued by the traditional algorithm. Sufficient statistics are stored in the nodes of the kd-tree. Then, an analysis of th...

Active Learning For Identifying Function Threshold Boundaries

Document Type: Paper
Tags: Active Learning, Astrostatistics, Gaussian Processes, Statistical Data Mining for Astrophysics, Applications

We present an efficient algorithm to actively select queries for learning the boundaries separating a function domain into regions where the function is above and below a given threshold. We develop experiment selection methods based on entropy, misclassification rate, variance, and their com...

Alexander Gray

Document Type: Person
Tags: Auton Fast Classifiers, Statistical Data Mining for Astrophysics, K Nearest Neighbor, Astrostatistics, Cached Sufficient Statistics, Clustering, Memory-based Learning, Efficient Statistical Algorithms, Life Science Data Mining, Locally Weighted Learning, Kernel Density Estimation, Bayesian Networks, Kd-trees and Ball-trees, Mixture Models, Optimization

Alex's fascinations in early grade school were Legos, breaking ciphers, and drawing human anatomy. After studying Applied Math and Computer Science at Berkeley, he resisted a job offer to do Hollywood special effects and ended up working at NASA's Jet Propulsion Laboratory for six years developi...

Andrew Moore

Document Type: Person
Tags: Link Analysis, Auton Fast Classifiers, Statistical Data Mining for Astrophysics, Cached Sufficient Statistics, Efficient Statistical Algorithms, Spatial Statistics, Life Science Data Mining, Logistic Regression, Locally Weighted Learning, GDA, AD-trees, Bayesian Networks, Kernel Density Estimation, Kd-trees and Ball-trees, Mixture Models, WSARE, Reinforcement Learning, Active Learning, Markov Decision Processes, K Nearest Neighbor, Astrostatistics, Clustering, Memory-based Learning, Biosurveillance, Applications, Optimization, Association Rules

Andrew began his career writing video-games for an obscure British personal computer. He rapidly became a thousandaire and retired to academia, where he received a PhD from the University of Cambridge in 1991. He researched robot learning as a Post-doc working with Chris Atkeson, and then moved ...

A tutorial on kd-trees

Document Type: Paper
Tags: Astrostatistics, Memory-based Learning, Kd-trees and Ball-trees

Extract from Andrew Moore's PhD Thesis. Gives a concise description of nearest neighbor search using kd-trees. See also Andrew's animations of KD-tree search algorithms.

Brent Bryan

Document Type: Person
Tags: Statistical Data Mining for Astrophysics, Astrostatistics, Applications, Active Learning

Ph.D. Machine Learning, Carnegie Mellon University, PA M.S. Statistical and Automated Learning, Carnegie Mellon University, PA M.Ph. Astronomy, Yale University, CT M.S. Astronomy, Yale University, CT B.A. Mathematics & Astronomy/Physics Whitman College, WA

Brigham Anderson

Document Type: Person
Tags: AD-trees, Statistical Data Mining for Astrophysics, Astrostatistics, Efficient Statistical Algorithms, Memory-based Learning, Applications, Optimization, Association Rules, Reinforcement Learning, Locally Weighted Learning, Active Learning

Condensed Representations for computationally tractable data mining of massive sky surveys

Document Type: Paper
Tags: Statistical Data Mining for Astrophysics, Cached Sufficient Statistics, Astrostatistics

Andrew Moore, Robert Nichol, Larry Wasserman, Andrew Connolly

Dan Pelleg

Document Type: Person
Tags: Statistical Data Mining for Astrophysics, Cached Sufficient Statistics, Astrostatistics, Clustering, Bayesian Networks, Efficient Statistical Algorithms, Kd-trees and Ball-trees, Mixture Models, Applications, Active Learning

Efficient Algorithms for Non-Parametric Clustering with Clutter

Document Type: Paper
Tags: Biosurveillance, Statistical Data Mining for Astrophysics, Astrostatistics, Clustering, Kernel Density Estimation, Efficient Statistical Algorithms, Memory-based Learning, Kd-trees and Ball-trees

Detecting and counting overdensities in data is a common problem in the physical and geographic sciences. One of the most successful of recent algorithms for the counting version of the problem was introduced by Cuevas, Febrero and Fraiman [Cuevas et al., 2000], which will be referred to as the ...