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» Application specific loss minimization using gradient boosti...
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113
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JMLR
2002
140views more  JMLR 2002»
15 years 24 days ago
On Boosting with Polynomially Bounded Distributions
We construct a framework which allows an algorithm to turn the distributions produced by some boosting algorithms into polynomially smooth distributions (w.r.t. the PAC oracle...
Nader H. Bshouty, Dmitry Gavinsky
144
Voted
ETVC
2008
15 years 2 months ago
Intrinsic Geometries in Learning
In a seminal paper, Amari (1998) proved that learning can be made more efficient when one uses the intrinsic Riemannian structure of the algorithms' spaces of parameters to po...
Richard Nock, Frank Nielsen
128
Voted
IPM
2008
100views more  IPM 2008»
15 years 1 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
103
Voted
ICIP
2009
IEEE
16 years 2 months ago
Early Terminating Algorithms For Adaboost Based Detectors
In this paper we propose an early termination algorithm for speeding up the detection phase of the Adaboost based detectors. In the basic algorithm, at a specific search location,...
CVPR
2004
IEEE
16 years 3 months ago
BoostMap: A Method for Efficient Approximate Similarity Rankings
This paper introduces BoostMap, a method that can significantly reduce retrieval time in image and video database systems that employ computationally expensive distance measures, ...
Vassilis Athitsos, Jonathan Alon, Stan Sclaroff, G...