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SIGIR
2002
ACM
13 years 4 months ago
Unsupervised document classification using sequential information maximization
We present a novel sequential clustering algorithm which is motivated by the Information Bottleneck (IB) method. In contrast to the agglomerative IB algorithm, the new sequential ...
Noam Slonim, Nir Friedman, Naftali Tishby
ICPR
2004
IEEE
14 years 5 months ago
Serialized Unsupervised Classifier for Adaptative Color Image Segmentation: Application to Digitized Ancient Manuscripts
This paper presents an adaptative algorithm for the segmentation of color images suited for document image analysis. The algorithm is based on a serialization of the k-means algor...
Frank Le Bourgeois, Hubert Emptoz, Yann Leydier
NIPS
2008
13 years 6 months ago
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification
Probabilistic topic models have become popular as methods for dimensionality reduction in collections of text documents or images. These models are usually treated as generative m...
Simon Lacoste-Julien, Fei Sha, Michael I. Jordan
AUSAI
2001
Springer
13 years 8 months ago
Fast Text Classification Using Sequential Sampling Processes
A central problem in information retrieval is the automated classification of text documents. While many existing methods achieve good levels of performance, they generally require...
Michael D. Lee
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
14 years 5 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler