159 search results - page 19 / 32 » Margin Maximizing Loss Functions |
NN
2000
Springer
14 years 11 months ago
2000
Springer
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
ICASSP
2011
IEEE
14 years 3 months ago
2011
IEEE
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
CIKM
2004
Springer
15 years 5 months ago
2004
Springer
Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. Standard machine learning techniques ...
APVIS
2009
15 years 24 days ago
2009
Direct volume rendering is an important tool for visualizing complex data sets. However, in the process of generating 2D images from 3D data, information is lost in the form of at...
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ICASSP
2011
IEEE
14 years 3 months ago
2011
IEEE
In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...