Genetic algorithms and support vector machines for time series classification D Eads, D Hill, S Davis, S Perkins, J Ma, R Porter, J Theiler Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary …, 2002 | 165 | 2002 |
Online feature selection for pixel classification K Glocer, D Eads, J Theiler Proceedings of the 22nd international conference on Machine learning, 249-256, 2005 | 59 | 2005 |
Grammar-guided feature extraction for time series classification D Eads, K Glocer, S Perkins, J Theiler Proceedings of the 9th Annual Conference on Neural Information Processing …, 2005 | 47 | 2005 |
Genie Pro: Robust image classification using shape, texture and spectral information S Perkins, K Edlund, D Esch-Mosher, D Eads, N Harvey, S Brumby Proc. SPIE Algorithms and Technologies for Multispectral, Hyperspectral, and …, 2005 | 36 | 2005 |
Towards a real‐time transient classification engine JS Bloom, DL Starr, NR Butler, P Nugent, M Rischard, D Eads, ... Astronomische Nachrichten 329 (3), 284-287, 2008 | 27 | 2008 |
hcluster: Hierarchical clustering for scipy D Eads | 21 | 2008 |
Weighted order statistic classifiers with large rank-order margin R Porter, D Eads, D Hush, J Theiler International Conference on Machine Learning 20 (2), 600-607, 2003 | 21 | 2003 |
SCALABLE, MEMORY-EFFICIENT MACHINE LEARNING AND PREDICTION FOR ENSEMBLES OF DECISION TREES FOR HOMOGENEOUS AND HETEROGENEOUS DATASETS DR Eads US Patent 20,140,337,269, 2014 | 17 | 2014 |
Unsupervised learning of tree alignment models for information extraction P Zigoris, D Eads, Y Zhang Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International …, 2006 | 17 | 2006 |
Feature extraction from multiple data sources using genetic programming JJ Szymanski, SP Brumby, P Pope, D Eads, D Esch-Mosher, M Galassi, ... Proceedings of SPIE 4725, 338-345, 2002 | 17 | 2002 |
SCALABLE, MEMORY-EFFICIENT MACHINE LEARNING AND PREDICTION FOR ENSEMBLES OF DECISION TREES FOR HOMOGENEOUS AND HETEROGENEOUS DATASETS DR Eads US Patent 20,140,337,255, 2014 | 10* | 2014 |
Graffiti: A framework for testing collaborative distributed metadata C Maltzahn, N Bobb, MW Storer, D Eads, SA Brandt, EL Miller In Proceedings in Informatics, 2007 | 8 | 2007 |
Multimodal approach to feature extraction for image and signal learning problems DR Eads, SJ Williams, J Theiler, R Porter, NR Harvey, SJ Perkins, ... PROCEEDINGS-SPIE THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING, 79-90, 2003 | 8 | 2003 |
Experiences using SciPy for computer vision research DR Eads, EJ Rosten Los Alamos National Laboratory (LANL), 2008 | 4 | 2008 |
Learning Object Location Predictors with Boosting and Grammar-Guided Feature Extraction D Eads, E Rosten, D Helmbold Arxiv preprint arXiv:0907.4354, 2009 | 3 | 2009 |
Boosting in Location Space D Eads, D Helmbold, E Rosten arXiv preprint arXiv:1309.1080, 2013 | 2 | 2013 |
WiseRFTM: A fast and scalable Random Forest D Eads, JW Richards, JS Bloom, H Brink, D Starr | 2* | |
Memory-Efficient Data Structures for Learning and Prediction D Eads, P Baines, JS Bloom | 1* | |
First time experiences using SciPy for computer vision research D Eads, E Rosten Los Alamos National Laboratory (LANL), 2008 | | 2008 |
Sparse Image Format DR Eads Los Alamos National Laboratory, 2007 | | 2007 |