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» Learning large margin classifiers locally and globally
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CVPR
2005
IEEE
14 years 9 months ago
A Statistical Field Model for Pedestrian Detection
This paper presents a new statistical model for detecting and tracking deformable objects such as pedestrians, where large shape variations induced by local shape deformation can ...
Ying Wu, Ting Yu, Gang Hua
SIAMIS
2010
378views more  SIAMIS 2010»
13 years 2 months ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert
KDD
2007
ACM
149views Data Mining» more  KDD 2007»
14 years 8 months ago
Distributed classification in peer-to-peer networks
This work studies the problem of distributed classification in peer-to-peer (P2P) networks. While there has been a significant amount of work in distributed classification, most o...
Ping Luo, Hui Xiong, Kevin Lü, Zhongzhi Shi
WWW
2009
ACM
14 years 8 months ago
Extracting article text from the web with maximum subsequence segmentation
Much of the information on the Web is found in articles from online news outlets, magazines, encyclopedias, review collections, and other sources. However, extracting this content...
Jeff Pasternack, Dan Roth
ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
13 years 5 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis