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    ICA
    2012
    Springer
    236views Signal Processing» more  ICA 2012»
    A Non-negative Approach to Language Informed Speech Separation
    12 years 3 months ago
    A Non-negative Approach to Language Informed Speech Separation
    Download  www.cs.illinois.edu
    Abstract. The use of high level information in source separation algorithms can greatly constrain the problem and lead to improved results by limiting the solution space to semanti...
    Gautham J. Mysore, Paris Smaragdis
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    ICCV
    2007
    IEEE
    275views Computer Vision» more  ICCV 2007»
    Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes
    14 years 9 months ago
    Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes
    Download  www.cs.berkeley.edu
    We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
    Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
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    EMNLP
    2009
    171views Natural Language Processing» more  EMNLP 2009»
    The infinite HMM for unsupervised PoS tagging
    13 years 5 months ago
    The infinite HMM for unsupervised PoS tagging
    Download  www.aclweb.org
    We extend previous work on fully unsupervised part-of-speech tagging. Using a non-parametric version of the HMM, called the infinite HMM (iHMM), we address the problem of choosing...
    Jurgen Van Gael, Andreas Vlachos, Zoubin Ghahraman...
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    BMCBI
    2005
    100views more  BMCBI 2005»
    Evolutionary models for insertions and deletions in a probabilistic modeling framework
    13 years 7 months ago
    Evolutionary models for insertions and deletions in a probabilistic modeling framework
    Download  www.biomedcentral.com
    Background: Probabilistic models for sequence comparison (such as hidden Markov models and pair hidden Markov models for proteins and mRNAs, or their context-free grammar counterp...
    Elena Rivas
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    ICML
    2007
    IEEE
    188views Machine Learning» more  ICML 2007»
    Multi-task learning for sequential data via iHMMs and the nested Dirichlet process
    14 years 8 months ago
    Multi-task learning for sequential data via iHMMs and the nested Dirichlet process
    Download  www.machinelearning.org
    A new hierarchical nonparametric Bayesian model is proposed for the problem of multitask learning (MTL) with sequential data. Sequential data are typically modeled with a hidden M...
    Kai Ni, Lawrence Carin, David B. Dunson
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