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» Variational Relevance Vector Machines
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ICCV
2003
IEEE
15 years 11 months ago
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...
BMCBI
2007
178views more  BMCBI 2007»
14 years 9 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
ICALP
2011
Springer
14 years 1 months ago
New Algorithms for Learning in Presence of Errors
We give new algorithms for a variety of randomly-generated instances of computational problems using a linearization technique that reduces to solving a system of linear equations...
Sanjeev Arora, Rong Ge
82
Voted
IPMI
2003
Springer
15 years 10 months ago
Feature Selection for Shape-Based Classification of Biological Objects
Abstract. In this paper, feature selection methodology from the machine learning literature is applied to the problem of shape-based classification. This methodology discards stati...
Paul A. Yushkevich, Sarang C. Joshi, Stephen M. Pi...
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
15 years 10 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims