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» Learning Gaussian Process Models from Uncertain Data
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114
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RECOMB
2000
Springer
15 years 6 months ago
Using Bayesian networks to analyze expression data
DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a "snapshot" of transcription levels within the c...
Nir Friedman, Michal Linial, Iftach Nachman, Dana ...
ICASSP
2010
IEEE
15 years 2 months ago
HMM-based separation of acoustic transfer function for single-channel sound source localization
This paper presents a sound source (talker) localization method using only a single microphone, where a HMM (Hidden Markov Model) of clean speech is introduced to estimate the aco...
Ryoichi Takashima, Tetsuya Takiguchi, Yasuo Ariki
121
Voted
ICDT
2010
ACM
219views Database» more  ICDT 2010»
15 years 12 months ago
Aggregate Queries for Discrete and Continuous Probabilistic XML
Sources of data uncertainty and imprecision are numerous. A way to handle this uncertainty is to associate probabilistic annotations to data. Many such probabilistic database mode...
Serge Abiteboul, T.-H Hubert Chan, Evgeny Kharlamo...
ECCV
2006
Springer
16 years 4 months ago
Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition
Abstract. In this paper we investigate a new method of learning partbased models for visual object recognition, from training data that only provides information about class member...
David J. Crandall, Daniel P. Huttenlocher
117
Voted
INTERSPEECH
2010
14 years 9 months ago
VAD-measure-embedded decoder with online model adaptation
We previously proposed a decoding method for automatic speech recognition utilizing hypothesis scores weighted by voice activity detection (VAD)-measures. This method uses two Gau...
Tasuku Oonishi, Koji Iwano, Sadaoki Furui