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ICML
2004
IEEE
14 years 9 months ago
Large margin hierarchical classification
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
Ofer Dekel, Joseph Keshet, Yoram Singer
TSP
2010
13 years 3 months ago
Learning graphical models for hypothesis testing and classification
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
COLING
2008
13 years 10 months ago
Exact Inference for Multi-label Classification using Sparse Graphical Models
This paper describes a parameter estimation method for multi-label classification that does not rely on approximate inference. It is known that multi-label classification involvin...
Yusuke Miyao, Jun-ichi Tsujii
ESANN
2008
13 years 10 months ago
Classification of chestnuts with feature selection by noise resilient classifiers
In this paper we solve the problem of classifying chestnut plants according to their place of origin. We compare the results obtained by state of the art classifiers, among which,...
Elena Roglia, Rossella Cancelliere, Rosa Meo
ICIP
2006
IEEE
14 years 10 months ago
Texture Classification with Ants
In this paper, we present a novel texture classification algorithm inspired by the self-assembling behavior of real ants when building live structures with their bodies. The propo...
Arshad Hussain, Nasir Rajpoot, Kashif Rajpoot