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» Learning Structured Models for Phone Recognition
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ICASSP
2011
IEEE
13 years 5 days ago
Learning and inference algorithms for partially observed structured switching vector autoregressive models
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
Balakrishnan Varadarajan, Sanjeev Khudanpur
NIPS
2001
13 years 9 months ago
Probabilistic principles in unsupervised learning of visual structure: human data and a model
To find out how the representations of structured visual objects depend on the co-occurrence statistics of their constituents, we exposed subjects to a set of composite images wit...
Shimon Edelman, Benjamin P. Hiles, Hwajin Yang, Na...
PERCOM
2003
ACM
14 years 1 months ago
Recognition of Human Activity through Hierarchical Stochastic Learning
Seeking to extend the functional capability of the elderly, we explore the use of probabilistic methods to learn and recognise human activity in order to provide monitoring suppor...
Sebastian Lühr, Hung Hai Bui, Svetha Venkates...
CLOR
2006
14 years 5 days ago
A Sparse Object Category Model for Efficient Learning and Complete Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
Robert Fergus, Pietro Perona, Andrew Zisserman
UM
2007
Springer
14 years 2 months ago
Inducing User Affect Recognition Models for Task-Oriented Environments
Accurately recognizing users’ affective states could contribute to more productive and enjoyable interactions, particularly for task-oriented learning environments. In addition t...
Sunyoung Lee, Scott W. McQuiggan, James C. Lester