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» Large-Scale Data Analysis Using Heuristic Methods
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ICML
1994
IEEE
15 years 8 months ago
Efficient Algorithms for Minimizing Cross Validation Error
Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected...
Andrew W. Moore, Mary S. Lee
DGO
2004
110views Education» more  DGO 2004»
15 years 6 months ago
Question Answering Performance on Table Data
Question answering (QA) on table data is a challenging information retrieval task. This paper describes a QA system for tables created with both machine learning and heuristic tab...
Xing Wei, W. Bruce Croft, David Pinto
CIMAGING
2008
141views Hardware» more  CIMAGING 2008»
15 years 6 months ago
Segmentation of digital microscopy data for the analysis of defect structures in materials using nonlinear diffusions
We apply stabilized inverse diffusion equations (SIDEs) to segment microscopy images of materials to aid in analysis of defects. We extend SIDE segmentation methods and demonstrat...
Landis M. Huffman, Jeff P. Simmons, Ilya Pollak
162
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IPPS
2010
IEEE
15 years 2 months ago
PreDatA - preparatory data analytics on peta-scale machines
Peta-scale scientific applications running on High End Computing (HEC) platforms can generate large volumes of data. For high performance storage and in order to be useful to scien...
Fang Zheng, Hasan Abbasi, Ciprian Docan, Jay F. Lo...
GECCO
2009
Springer
146views Optimization» more  GECCO 2009»
15 years 11 months ago
Analyzing the landscape of a graph based hyper-heuristic for timetabling problems
Hyper-heuristics can be thought of as “heuristics to choose heuristics”. They are concerned with adaptively finding solution methods, rather than directly producing a solutio...
Gabriela Ochoa, Rong Qu, Edmund K. Burke