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» Learning Probabilistic Models of Relational Structure
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ICASSP
2011
IEEE
14 years 4 months ago
Enriching Mandarin speech recognition by incorporating a hierarchical prosody model
This paper presents a new probabilistic framework of Mandarin speech recognition by incorporating a sophisticated hierarchical prosody model into the conventional HMM-based system...
Jyh-Her Yang, Ming-Chieh Liu, Hao-Hsiang Chang, Ch...
BMCBI
2010
140views more  BMCBI 2010»
14 years 10 months ago
An improved machine learning protocol for the identification of correct Sequest search results
Background: Mass spectrometry has become a standard method by which the proteomic profile of cell or tissue samples is characterized. To fully take advantage of tandem mass spectr...
Morten Kallberg, Hui Lu
JMLR
2008
144views more  JMLR 2008»
15 years 16 days ago
Search for Additive Nonlinear Time Series Causal Models
Pointwise consistent, feasible procedures for estimating contemporaneous linear causal structure from time series data have been developed using multiple conditional independence ...
Tianjiao Chu, Clark Glymour
75
Voted
ATAL
2005
Springer
15 years 6 months ago
Modeling complex multi-issue negotiations using utility graphs
This paper presents an agent strategy for complex bilateral negotiations over many issues with inter-dependent valuations. We use ideas inspired by graph theory and probabilistic ...
Valentin Robu, D. J. A. Somefun, Johannes A. La Po...
106
Voted
PAMI
2010
205views more  PAMI 2010»
14 years 11 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille