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» Learning SVMs from Sloppily Labeled Data
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MCS
2005
Springer
14 years 2 months ago
Exploiting Class Hierarchies for Knowledge Transfer in Hyperspectral Data
Abstract. Obtaining ground truth for hyperspectral data is an expensive task. In addition, a number of factors cause the spectral signatures of the same class to vary with location...
Suju Rajan, Joydeep Ghosh
SIGIR
2008
ACM
13 years 9 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
ICDM
2009
IEEE
142views Data Mining» more  ICDM 2009»
13 years 7 months ago
Building Classifiers with Independency Constraints
In this paper we study the problem of classifier learning where the input data contains unjustified dependencies between some data attributes and the class label. Such cases arise...
Toon Calders, Faisal Kamiran, Mykola Pechenizkiy
SADM
2010
128views more  SADM 2010»
13 years 7 months ago
Online training on a budget of support vector machines using twin prototypes
: This paper proposes twin prototype support vector machine (TVM), a constant space and sublinear time support vector machine (SVM) algorithm for online learning. TVM achieves its ...
Zhuang Wang, Slobodan Vucetic
VLSID
2007
IEEE
97views VLSI» more  VLSID 2007»
14 years 3 months ago
Embedded Support Vector Machine : Architectural Enhancements and Evaluation
In recent years, research and development in the field of machine learning and classification techniques have gained paramount importance. The future generation of intelligent e...
Soumyajit Dey, Monu Kedia, Niket Agarwal, Anupam B...