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CVPR
2004
IEEE
16 years 6 months ago
Is Bottom-Up Attention Useful for Object Recognition?
A key problem in learning multiple objects from unlabeled images is that it is a priori impossible to tell which part of the image corresponds to each individual object, and which...
Ueli Rutishauser, Dirk Walther, Christof Koch, Pie...
ICPR
2008
IEEE
16 years 6 months ago
Extraction of shoe-print patterns from impression evidence using Conditional Random Fields
Impression evidence in the form of shoe-prints are commonly found in crime scenes. A critical step in automatic shoe-print identification is extraction of the shoe-print pattern. ...
Sargur N. Srihari, Veshnu Ramakrishnan
COLT
1998
Springer
15 years 9 months ago
Large Margin Classification Using the Perceptron Algorithm
We introduce and analyze a new algorithm for linear classification which combines Rosenblatt's perceptron algorithm with Helmbold and Warmuth's leave-one-out method. Like...
Yoav Freund, Robert E. Schapire
ICDCS
2007
IEEE
15 years 11 months ago
Distributed Density Estimation Using Non-parametric Statistics
Learning the underlying model from distributed data is often useful for many distributed systems. In this paper, we study the problem of learning a non-parametric model from distr...
Yusuo Hu, Hua Chen, Jian-Guang Lou, Jiang Li
ICPR
2004
IEEE
16 years 5 months ago
Relevant Linear Feature Extraction Using Side-information and Unlabeled Data
"Learning with side-information" is attracting more and more attention in machine learning problems. In this paper, we propose a general iterative framework for relevant...
Changshui Zhang, Fei Wu, Yonglei Zhou