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» Feature selection in scientific applications
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CLOUDCOM
2010
Springer
13 years 7 months ago
Efficient Metadata Generation to Enable Interactive Data Discovery over Large-Scale Scientific Data Collections
Discovering the correct dataset efficiently is critical for computations and effective simulations in scientific experiments. In contrast to searching web documents over the Intern...
Sangmi Lee Pallickara, Shrideep Pallickara, Milija...
AAAI
2004
13 years 11 months ago
Spatial Aggregation for Qualitative Assessment of Scientific Computations
Qualitative assessment of scientific computations is an emerging application area that applies a data-driven approach to characterize, at a high level, phenomena including conditi...
Chris Bailey-Kellogg, Naren Ramakrishnan
HCW
2000
IEEE
14 years 2 months ago
Heterogeneity as Key Feature of High Performance Computing: the PQE1 Prototype
In this work we present the results of a project aimed at assembling an hybrid massively parallel machine, the PQE1 prototype, devoted to the simulation of complex physical models...
Paolo Palazzari, Lidia Arcipiani, Massimo Celino, ...
ICB
2007
Springer
185views Biometrics» more  ICB 2007»
14 years 4 months ago
Biometric Hashing Based on Genetic Selection and Its Application to On-Line Signatures
We present a general biometric hash generation scheme based on vector quantization of multiple feature subsets selected with genetic optimization. The quantization of subsets overc...
Manuel R. Freire, Julian Fiérrez-Aguilar, J...
ICDM
2003
IEEE
143views Data Mining» more  ICDM 2003»
14 years 3 months ago
Active Sampling for Feature Selection
In knowledge discovery applications, where new features are to be added, an acquisition policy can help select the features to be acquired based on their relevance and the cost of...
Sriharsha Veeramachaneni, Paolo Avesani