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IDA
2001
Springer
13 years 10 months ago
An Algorithm for Segmenting Categorical Time Series into Meaningful Episodes
This paper describes an unsupervised algorithm for segmenting categorical time series. The algorithm first collects statistics about the frequency and boundary entropy of ngrams, t...
Paul R. Cohen, Niall M. Adams
CVPR
2009
IEEE
14 years 11 months ago
D - Clutter: Building object model library from unsupervised segmentation of cluttered scenes
Autonomous systems which learn and utilize a limited visual vocabulary have wide spread applications. Enabling such systems to segment a set of cluttered scenes into objects is ...
Chandra Kambhamettu, Dimitris N. Metaxas, Gowri So...
ICDM
2002
IEEE
130views Data Mining» more  ICDM 2002»
13 years 10 months ago
Unsupervised Segmentation of Categorical Time Series into Episodes
This paper describes an unsupervised algorithm for segmenting categorical time series into episodes. The VOTING-EXPERTS algorithm first collects statistics about the frequency an...
Paul R. Cohen, Brent Heeringa, Niall M. Adams
IPAS
2010
13 years 3 months ago
An unsupervised learning approach for facial expression recognition using semi-definite programming and generalized principal co
In this paper, we consider facial expression recognition using an unsupervised learning framework. Specifically, given a data set composed of a number of facial images of the same...
Behnood Gholami, Wassim M. Haddad, Allen Tannenbau...
ECCV
2008
Springer
14 years 7 months ago
Weakly Supervised Object Localization with Stable Segmentations
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...