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JMLR
2008
230views more  JMLR 2008»
15 years 5 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
ICCV
2009
IEEE
16 years 10 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
CVPR
2006
IEEE
16 years 7 months ago
Recursive estimation of generative models of video
In this paper we present a generative model and learning procedure for unsupervised video clustering into scenes. The work addresses two important problems: realistic modeling of ...
Nemanja Petrovic, Aleksandar Ivanovic, Nebojsa Joj...
CVPR
2006
IEEE
16 years 7 months ago
Image-Based Multiclass Boosting and Echocardiographic View Classification
We tackle the problem of automatically classifying cardiac view for an echocardiographic sequence as a multiclass object detection. As a solution, we present an imagebased multicl...
Shaohua Kevin Zhou, J. H. Park, Bogdan Georgescu, ...
CVPR
2007
IEEE
16 years 7 months ago
Incremental Linear Discriminant Analysis Using Sufficient Spanning Set Approximations
This paper presents a new incremental learning solution for Linear Discriminant Analysis (LDA). We apply the concept of the sufficient spanning set approximation in each update st...
Björn Stenger, Josef Kittler, Roberto Cipolla...