Skip to search form
Skip to main content
Skip to account menu
Semantic Scholar
Semantic Scholar's Logo
Search 229,751,562 papers from all fields of science
Search
Sign In
Create Free Account
Boosting (machine learning)
Known as:
Boost
, Boosting (meta-algorithm)
, Boosting methods for object categorization
Boosting is a machine learning ensemble meta-algorithm for primarily reducing bias, and also variance in supervised learning, and a family of machine…
Expand
Wikipedia
(opens in a new tab)
Create Alert
Alert
Related topics
Related topics
41 relations
AdaBoost
Alternating decision tree
Bias–variance tradeoff
Bootstrap aggregating
Expand
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2014
Highly Cited
2014
Word Channel Based Multiscale Pedestrian Detection without Image Resizing and Using Only One Classifier
A. Costea
,
S. Nedevschi
IEEE Conference on Computer Vision and Pattern…
2014
Corpus ID: 16294447
Most pedestrian detection approaches that achieve high accuracy and precision rate and that can be used for realtime applications…
Expand
2013
2013
Empirical analysis of model selection criteria for genetic programming in modeling of time series system
A. Garg
,
S. Sriram
,
K. Tai
IEEE Conference on Computational Intelligence for…
2013
Corpus ID: 14801777
Genetic programming (GP) and its variants have been extensively applied for modeling of the stock markets. To improve the…
Expand
2012
2012
New Estimates of Real Income and Multifactor Productivity Growth for the Canadian Business Sector, 1961-2011
W. Diewert
,
Emily Yu
2012
Corpus ID: 55156712
Using new data from Statistics Canada, this article shows that the multifactor productivity (MFP) performance of the Canadian…
Expand
2011
2011
Boosted Learning of Visual Word Weighting Factors for Bag-of-Features Based Medical Image Retrieval
Jingyan Wang
,
Yongping Li
,
Y. Zhang
,
Honglan Xie
,
Chao Wang
Sixth International Conference on Image and…
2011
Corpus ID: 18805660
In this paper, we investigate the bag-of-feature based medical image retrieval methods, which represent an image as a bag of…
Expand
2008
2008
Real-time side vehicle tracking using parts-based boosting
Wen-Chung Chang
,
Chih-Wei Cho
IEEE International Conference on Systems, Man and…
2008
Corpus ID: 22471937
This paper presents a real-time vision-based side vehicle detection system employing a parts-based boosting algorithm. Working at…
Expand
2003
2003
Texture classification of logged forests in tropical Africa using machine-learning algorithms
Jonathan Cheung-Wai Chan
,
N. Laporte
,
Ruth S. DeFries
2003
Corpus ID: 2772407
This Letter describes a procedure that incorporates textural measures in the classification of logged forests from Landsat…
Expand
Highly Cited
2003
Highly Cited
2003
Learning cross-document structural relationships using boosting
Zhu Zhang
,
Jahna Otterbacher
,
Dragomir R. Radev
International Conference on Information and…
2003
Corpus ID: 7609831
Multi-document discoure analysis has emerged with the potential of improving various information retrieval applications. Based on…
Expand
2003
2003
Fast Face Detection Using AdaBoost
Julien Meynet
,
Vlad Popovici
,
J. Thiran
2003
Corpus ID: 1017280
Keywords: face_det ; lts5 Reference EPFL-STUDENT-86954 Record created on 2006-06-14, modified on 2017-05-10
2002
2002
Channel assignment strategies for a high altitude platform spot-beam architecture
D. Grace
,
C. Spillard
,
J. Thornton
,
T. Tozer
IEEE International Symposium on Personal, Indoor…
2002
Corpus ID: 17172161
Channel assignment strategies for use with a high altitude platform spot beam architecture are examined. A novel power roll-off…
Expand
1993
1993
Redressing the balance: the advantages of informal evaluation techniques for Intelligent Learning Environments
M. Twidale
1993
Corpus ID: 13894895
The paper discusses issues to be considered when evaluating an Intelligent Learning Environment. In particular it considers…
Expand
By clicking accept or continuing to use the site, you agree to the terms outlined in our
Privacy Policy
(opens in a new tab)
,
Terms of Service
(opens in a new tab)
, and
Dataset License
(opens in a new tab)
ACCEPT & CONTINUE