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» Melody Spotting Using Hidden Markov Models
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80
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ICASSP
2011
IEEE
14 years 3 months ago
A new method for visual stylometry on impressionist paintings
A new emerging field, that of visual stylometry of art, proposes to apply image analysis and machine learning tools to high-resolution digital images of artwork in order to assis...
Hanchao Qi, Shannon Hughes
113
Voted
ACL
2008
15 years 1 months ago
Unsupervised Learning of Acoustic Sub-word Units
Accurate unsupervised learning of phonemes of a language directly from speech is demonstrated via an algorithm for joint unsupervised learning of the topology and parameters of a ...
Balakrishnan Varadarajan, Sanjeev Khudanpur, Emman...
SDM
2007
SIAM
184views Data Mining» more  SDM 2007»
15 years 1 months ago
Mining Naturally Smooth Evolution of Clusters from Dynamic Data
Many clustering algorithms have been proposed to partition a set of static data points into groups. In this paper, we consider an evolutionary clustering problem where the input d...
Yi Wang, Shi-Xia Liu, Jianhua Feng, Lizhu Zhou
107
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BMCBI
2008
137views more  BMCBI 2008»
14 years 11 months ago
A dynamic Bayesian network approach to protein secondary structure prediction
Background: Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful informatio...
Xin-Qiu Yao, Huaiqiu Zhu, Zhen-Su She
107
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SIGMETRICS
2010
ACM
195views Hardware» more  SIGMETRICS 2010»
15 years 3 months ago
CWS: a model-driven scheduling policy for correlated workloads
We define CWS, a non-preemptive scheduling policy for workloads with correlated job sizes. CWS tackles the scheduling problem by inferring the expected sizes of upcoming jobs bas...
Giuliano Casale, Ningfang Mi, Evgenia Smirni