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PERVASIVE
2006
Springer
13 years 7 months ago
Building Reliable Activity Models Using Hierarchical Shrinkage and Mined Ontology
Abstract. Activity inference based on object use has received considerable recent attention. Such inference requires statistical models that map activities to the objects used in p...
Emmanuel Munguia Tapia, Tanzeem Choudhury, Matthai...
NIPS
2003
13 years 9 months ago
Learning the k in k-means
When clustering a dataset, the right number k of clusters to use is often not obvious, and choosing k automatically is a hard algorithmic problem. In this paper we present an impr...
Greg Hamerly, Charles Elkan
ICDM
2003
IEEE
119views Data Mining» more  ICDM 2003»
14 years 25 days ago
A Dynamic Adaptive Self-Organising Hybrid Model for Text Clustering
Clustering by document concepts is a powerful way of retrieving information from a large number of documents. This task in general does not make any assumption on the data distrib...
Chihli Hung, Stefan Wermter
SDM
2008
SIAM
177views Data Mining» more  SDM 2008»
13 years 9 months ago
Cluster Ensemble Selection
This paper studies the ensemble selection problem for unsupervised learning. Given a large library of different clustering solutions, our goal is to select a subset of solutions t...
Xiaoli Z. Fern, Wei Lin
NIPS
2007
13 years 9 months ago
Hierarchical Penalization
Hierarchical penalization is a generic framework for incorporating prior information in the fitting of statistical models, when the explicative variables are organized in a hiera...
Marie Szafranski, Yves Grandvalet, Pierre Morizet-...