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NIPS
2007
13 years 8 months ago
A General Boosting Method and its Application to Learning Ranking Functions for Web Search
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier C...
ICML
2004
IEEE
14 years 8 months ago
Boosting margin based distance functions for clustering
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
PAMI
2008
208views more  PAMI 2008»
13 years 7 months ago
BoostMap: An Embedding Method for Efficient Nearest Neighbor Retrieval
This paper describes BoostMap, a method for efficient nearest neighbor retrieval under computationally expensive distance measures. Database and query objects are embedded into a v...
Vassilis Athitsos, Jonathan Alon, Stan Sclaroff, G...
TCSV
2008
313views more  TCSV 2008»
13 years 7 months ago
Fast Pedestrian Detection Using a Cascade of Boosted Covariance Features
Efficiently and accurately detecting pedestrians plays a very important role in many computer vision applications such as video surveillance and smart cars. In order to find the ri...
Sakrapee Paisitkriangkrai, Chunhua Shen, Jian Zhan...
CVPR
2004
IEEE
14 years 9 months ago
Learning Distance Functions for Image Retrieval
Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall