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ICML
2006
IEEE
16 years 5 months ago
Accelerated training of conditional random fields with stochastic gradient methods
We apply Stochastic Meta-Descent (SMD), a stochastic gradient optimization method with gain vector adaptation, to the training of Conditional Random Fields (CRFs). On several larg...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark ...
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COLT
2007
Springer
15 years 11 months ago
On-Line Estimation with the Multivariate Gaussian Distribution
We consider on-line density estimation with the multivariate Gaussian distribution. In each of a sequence of trials, the learner must posit a mean µ and covariance Σ; the learner...
Sanjoy Dasgupta, Daniel Hsu
ICANN
2003
Springer
15 years 10 months ago
A Comparison of Model Aggregation Methods for Regression
Combining machine learning models is a means of improving overall accuracy.Various algorithms have been proposed to create aggregate models from other models, and two popular examp...
Zafer Barutçuoglu
COLT
2006
Springer
15 years 8 months ago
Online Tracking of Linear Subspaces
We address the problem of online de-noising a stream of input points. We assume that the clean data is embedded in a linear subspace. We present two online algorithms for tracking ...
Koby Crammer
ESANN
2003
15 years 6 months ago
Neural Networks and M5 model trees in modeling water level-discharge relationship for an Indian river
: In flood management it is important to reliably estimate the discharge in a river. Hydrologists use historic data to establish a rating curve – a relationship between the water...
Biswanath Bhattacharya, Dimitri P. Solomatine