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Damian Eads
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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
1642002
Online feature selection for pixel classification
K Glocer, D Eads, J Theiler
Proceedings of the 22nd international conference on Machine learning, 249-256, 2005
592005
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
472005
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
362005
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
272008
hcluster: Hierarchical clustering for scipy
D Eads
212008
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
212003
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
172014
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
172006
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
172002
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
82007
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
82003
Experiences using SciPy for computer vision research
DR Eads, EJ Rosten
Los Alamos National Laboratory (LANL), 2008
42008
Learning Object Location Predictors with Boosting and Grammar-Guided Feature Extraction
D Eads, E Rosten, D Helmbold
Arxiv preprint arXiv:0907.4354, 2009
32009
Boosting in Location Space
D Eads, D Helmbold, E Rosten
arXiv preprint arXiv:1309.1080, 2013
22013
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
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