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CIKM
2009
Springer
14 years 2 months ago
Feature selection for ranking using boosted trees
Modern search engines have to be fast to satisfy users, so there are hard back-end latency requirements. The set of features useful for search ranking functions, though, continues...
Feng Pan, Tim Converse, David Ahn, Franco Salvetti...
ICMCS
2006
IEEE
153views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Learning-Based Interactive Video Retrieval System
This paper presents an interactive video event retrieval system based on improved adaboost learning. This system consists of three main steps. Firstly, a long video sequence is pa...
Chi-Jiunn Wu, Hui-Chi Zeng, Szu-Hao Huang, Shang-H...
ICCV
2005
IEEE
14 years 1 months ago
Contour-Based Learning for Object Detection
We present a novel categorical object detection scheme that uses only local contour-based features. A two-stage, partially supervised learning architecture is proposed: a rudiment...
Jamie Shotton, Andrew Blake, Roberto Cipolla
ICML
2000
IEEE
14 years 8 months ago
FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness
Most machine learning algorithms are lazy: they extract from the training set the minimum information needed to predict its labels. Unfortunately, this often leads to models that ...
Joseph O'Sullivan, John Langford, Rich Caruana, Av...
IROS
2007
IEEE
158views Robotics» more  IROS 2007»
14 years 1 months ago
Feature selection in conditional random fields for activity recognition
Abstract— Temporal classification, such as activity recognition, is a key component for creating intelligent robot systems. In the case of robots, classification algorithms mus...
Douglas L. Vail, John D. Lafferty, Manuela M. Velo...