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NIPS
2007
13 years 10 months ago
Regularized Boost for Semi-Supervised Learning
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
Ke Chen 0001, Shihai Wang
GECCO
1999
Springer
133views Optimization» more  GECCO 1999»
14 years 1 months ago
Evolution of Goal-Directed Behavior from Limited Information in a Complex Environment
In this paper, we apply an evolutionary algorithm to learning behavior on a novel, interesting task to explore the general issue of learning e ective behaviors in a complex enviro...
Matthew R. Glickman, Katia P. Sycara
ICPR
2000
IEEE
14 years 10 months ago
Visual Extraction of Motion-Based Information from Image Sequences
We describe a system which is designed to assist in extracting high-level information from sets or sequences of images. We show that the method of principal components analysis fo...
David P. Gibson, Neill W. Campbell, Colin J. Dalto...
CORR
2002
Springer
99views Education» more  CORR 2002»
13 years 8 months ago
The Identification of Context-Sensitive Features: A Formal Definition of Context for Concept Learning
A large body of research in machine learning is concerned with supervised learning from examples. The examples are typically represented as vectors in a multi-dimensional feature ...
Peter D. Turney
ESWA
2008
173views more  ESWA 2008»
13 years 9 months ago
Image semantics discovery from web pages for semantic-based image retrieval using self-organizing maps
Traditional content-based image retrieval (CBIR) systems often fail to meet a user's need due to the `semantic gap' between the extracted features of the systems and the...
Hsin-Chang Yang, Chung-Hong Lee