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CIARP
2004
Springer
13 years 11 months ago
Unsupervised Learning of Ontology-Linked Selectional Preferences
We present a method for extracting selectional preferences of verbs from unannotated text. These selectional preferences are linked to an ontology (e.g. the hypernym relations foun...
Hiram Calvo, Alexander F. Gelbukh
ICCV
2011
IEEE
12 years 6 months ago
Domain Adaptation for Object Recognition: An Unsupervised Approach
Adapting the classifier trained on a source domain to recognize instances from a new target domain is an important problem that is receiving recent attention. In this paper, we p...
Raghuraman Gopalan, Ruonan Li, Rama Chellappa
ICCV
2005
IEEE
13 years 11 months ago
LOCUS: Learning Object Classes with Unsupervised Segmentation
We address the problem of learning object class models and object segmentations from unannotated images. We introduce LOCUS (Learning Object Classes with Unsupervised Segmentation...
John M. Winn, Nebojsa Jojic
PAMI
2008
170views more  PAMI 2008»
13 years 6 months ago
Unsupervised Category Modeling, Recognition, and Segmentation in Images
Suppose a set of arbitrary (unlabeled) images contains frequent occurrences of 2D objects from an unknown category. This paper is aimed at simultaneously solving the following rel...
Sinisa Todorovic, Narendra Ahuja
PKDD
2009
Springer
148views Data Mining» more  PKDD 2009»
14 years 15 days ago
Feature Selection by Transfer Learning with Linear Regularized Models
Abstract. This paper presents a novel feature selection method for classification of high dimensional data, such as those produced by microarrays. It includes a partial supervisio...
Thibault Helleputte, Pierre Dupont