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» Modeling Classification and Inference Learning
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ADAC
2007
58views more  ADAC 2007»
13 years 8 months ago
Generalized mixture models, semi-supervised learning, and unknown class inference
In this paper, we discuss generalized mixture models and related semi-supervised learning methods, and show how they can be used to provide explicit methods for unknown class infer...
Samuel J. Frame, Sreenivasa Rao Jammalamadaka
NIPS
2004
13 years 9 months ago
Semi-supervised Learning on Directed Graphs
Given a directed graph in which some of the nodes are labeled, we investigate the question of how to exploit the link structure of the graph to infer the labels of the remaining u...
Dengyong Zhou, Bernhard Schölkopf, Thomas Hof...
ISBI
2006
IEEE
14 years 8 months ago
A novel approximate inference approach to automated classification of protein subcellular location patterns in multi-cell images
The subcellular location of proteins is most often determined by visual interpretation of fluorescence microscope images. In recent years, automated systems have been developed so...
Shann-Ching Chen, Geoffrey J. Gordon, Robert F. Mu...
NIPS
1998
13 years 9 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
ALT
2006
Springer
14 years 4 months ago
The Complexity of Learning SUBSEQ (A)
Higman showed that if A is any language then SUBSEQ(A) is regular, where SUBSEQ(A) is the language of all subsequences of strings in A. We consider the following inductive inferenc...
Stephen A. Fenner, William I. Gasarch