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» Predicting relative performance of classifiers from samples
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SC
2004
ACM
15 years 6 months ago
A Performance and Scalability Analysis of the BlueGene/L Architecture
This paper is structured as follows. Section 2 gives an architectural description of BlueGene/L. Section 3 analyzes the issue of “computational noise” – the effect that the o...
Kei Davis, Adolfy Hoisie, Greg Johnson, Darren J. ...
105
Voted
GECCO
2005
Springer
102views Optimization» more  GECCO 2005»
15 years 6 months ago
Evolutionary rule-based system for IPO underpricing prediction
Academic literature has documented for a long time the existence of important price gains in the first trading day of initial public offerings (IPOs). Most of the empirical analys...
David Quintana, Cristóbal Luque del Arco-Ca...
CEAS
2007
Springer
15 years 4 months ago
Online Active Learning Methods for Fast Label-Efficient Spam Filtering
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
D. Sculley
91
Voted
ICPR
2010
IEEE
14 years 10 months ago
Improving Classification Accuracy by Comparing Local Features through Canonical Correlations
Classifying images using features extracted from densely sampled local patches has enjoyed significant success in many detection and recognition tasks. It is also well known that ...
Mert Dikmen, Thomas S. Huang
227
Voted
ICDE
2009
IEEE
157views Database» more  ICDE 2009»
16 years 2 months ago
A Rule-Based Classification Algorithm for Uncertain Data
Abstract-- Data uncertainty is common in real-world applications due to various causes, including imprecise measurement, network latency, outdated sources and sampling errors. Thes...
Biao Qin, Yuni Xia, Sunil Prabhakar, Yi-Cheng Tu