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ICML
2008
IEEE
16 years 4 months ago
Boosting with incomplete information
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we pres...
Feng Jiao, Gholamreza Haffari, Greg Mori, Shaojun ...
ECML
2004
Springer
15 years 9 months ago
Exploiting Unlabeled Data in Content-Based Image Retrieval
Abstract. In this paper, the Ssair (Semi-Supervised Active Image Retrieval) approach, which attempts to exploit unlabeled data to improve the performance of content-based image ret...
Zhi-Hua Zhou, Ke-Jia Chen, Yuan Jiang
WWW
2010
ACM
15 years 11 months ago
A scalable machine-learning approach for semi-structured named entity recognition
Named entity recognition studies the problem of locating and classifying parts of free text into a set of predefined categories. Although extensive research has focused on the de...
Utku Irmak, Reiner Kraft
ICCV
2005
IEEE
16 years 6 months ago
A Generative/Discriminative Learning Algorithm for Image Classification
We have developed a two-phase generative / discriminative learning procedure for the recognition of classes of objects and concepts in outdoor scenes. Our method uses both multipl...
Yi Li, Linda G. Shapiro, Jeff A. Bilmes
ECCV
2006
Springer
16 years 6 months ago
Learning Compositional Categorization Models
Abstract. This contribution proposes a compositional approach to visual object categorization of scenes. Compositions are learned from the Caltech 101 database1 intermediate abstra...
Björn Ommer, Joachim M. Buhmann