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» A Bayesian Approach to Semi-Supervised Learning
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TSP
2011
230views more  TSP 2011»
13 years 3 months ago
Bayesian Nonparametric Inference of Switching Dynamic Linear Models
—Many complex dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
BMCBI
2008
107views more  BMCBI 2008»
13 years 8 months ago
A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
Background: A better understanding of the mechanisms involved in gas-phase fragmentation of peptides is essential for the development of more reliable algorithms for high-throughp...
Cong Zhou, Lucas D. Bowler, Jianfeng Feng
ICDAR
2003
IEEE
14 years 2 months ago
Character Recognition by Adaptive Statistical Similarity
Handwriting recognition and OCR systems need to cope with a wide variety of writing styles and fonts, many of them possibly not previously encountered during training. This paper d...
Thomas M. Breuel
ICML
2005
IEEE
14 years 9 months ago
Computational aspects of Bayesian partition models
The conditional distribution of a discrete variable y, given another discrete variable x, is often specified by assigning one multinomial distribution to each state of x. The cost...
Mikko Koivisto, Kismat Sood
PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
14 years 3 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone