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BMCBI
2006
137views more  BMCBI 2006»
13 years 7 months ago
A classification-based framework for predicting and analyzing gene regulatory response
Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...
ALT
2004
Springer
14 years 4 months ago
Learning r-of-k Functions by Boosting
We investigate further improvement of boosting in the case that the target concept belongs to the class of r-of-k threshold Boolean functions, which answer “+1” if at least r o...
Kohei Hatano, Osamu Watanabe
JCIT
2010
162views more  JCIT 2010»
13 years 2 months ago
Traffic Prediction Based on Improved Neural Network
Artificial neural networks and genetic algorithms derived from the corresponding simulation of biology, anatomy. The paper analyzes the advantages and the disadvantages of the art...
Jian-ming Cui
CVPR
2008
IEEE
14 years 9 months ago
Boosting adaptive linear weak classifiers for online learning and tracking
Online boosting methods have recently been used successfully for tracking, background subtraction etc. Conventional online boosting algorithms emphasize on interchanging new weak ...
Toufiq Parag, Fatih Porikli, Ahmed M. Elgammal
GIS
2010
ACM
13 years 6 months ago
Location disambiguation in local searches using gradient boosted decision trees
Local search is a specialization of the web search that allows users to submit geographically constrained queries. However, one of the challenges for local search engines is to un...
Ritesh Agrawal, James G. Shanahan