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» Predicting relative performance of classifiers from samples
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SIGIR
2002
ACM
13 years 7 months ago
Predicting query performance
We develop a method for predicting query performance by computing the relative entropy between a query language model and the corresponding collection language model. The resultin...
Stephen Cronen-Townsend, Yun Zhou, W. Bruce Croft
ICPR
2006
IEEE
14 years 8 months ago
Statistical Model for the Classification of the Wavelet Transforms of T-ray Pulses
This study applies Auto Regressive (AR) and Auto Regressive Moving Average (ARMA) modeling to wavelet decomposed terahertz pulsed signals to assist biomedical diagnosis and mail/p...
Bradley Ferguson, Brian Wai-Him Ng, Derek Abbott, ...
SDM
2004
SIAM
174views Data Mining» more  SDM 2004»
13 years 9 months ago
Classifying Documents Without Labels
Automatic classification of documents is an important area of research with many applications in the fields of document searching, forensics and others. Methods to perform classif...
Daniel Barbará, Carlotta Domeniconi, Ning K...
ICDM
2003
IEEE
220views Data Mining» more  ICDM 2003»
14 years 27 days ago
Exploiting Unlabeled Data for Improving Accuracy of Predictive Data Mining
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
14 years 8 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos