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» A Spectral Algorithm for Learning Hidden Markov Models
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NIPS
2001
13 years 9 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
DAS
2010
Springer
13 years 9 months ago
Overlapped text segmentation using Markov random field and aggregation
Separating machine printed text and handwriting from overlapping text is a challenging problem in the document analysis field and no reliable algorithms have been developed thus f...
Xujun Peng, Srirangaraj Setlur, Venu Govindaraju, ...
DAGM
2011
Springer
12 years 7 months ago
Relaxed Exponential Kernels for Unsupervised Learning
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la...
ICASSP
2011
IEEE
12 years 11 months ago
Informative dialect recognition using context-dependent pronunciation modeling
We propose an informative dialect recognition system that learns phonetic transformation rules, and uses them to identify dialects. A hidden Markov model is used to align referenc...
Nancy F. Chen, Wade Shen, Joseph P. Campbell, Pedr...
ICPR
2004
IEEE
14 years 8 months ago
Joint Spatial and Temporal Structure Learning for Task based Control
We present an example of a joint spatial and temporal task learning algorithm that results in a generative model that has applications for on-line visual control. We review work o...
Hilary Buxton, Kingsley Sage