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ICCV
2005
IEEE
16 years 8 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
ICML
2000
IEEE
16 years 7 months ago
Constructive Feature Learning and the Development of Visual Expertise
We present a framework for learning features for visual discrimination. The learning system is exposed to a sequence of training images. Whenever it fails to recognize a visual co...
Justus H. Piater, Roderic A. Grupen
ICDM
2007
IEEE
187views Data Mining» more  ICDM 2007»
16 years 1 months ago
A Comparative Study of Methods for Transductive Transfer Learning
The problem of transfer learning, where information gained in one learning task is used to improve performance in another related task, is an important new area of research. While...
Andrew Arnold, Ramesh Nallapati, William W. Cohen
QSIC
2007
IEEE
16 years 1 months ago
Learning Effective Oracle Comparator Combinations for Web Applications
Web application testers need automated, effective approaches to validate the test results of complex, evolving web applications. In previous work, we developed a suite of automate...
Sara Sprenkle, Emily Hill, Lori L. Pollock
AAAI
2008
15 years 9 months ago
Transfer Learning via Dimensionality Reduction
Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a target domain, even when the train...
Sinno Jialin Pan, James T. Kwok, Qiang Yang