146 search results - page 10 / 30 » Online Gradient Descent Learning Algorithms |
NIPS
1998
13 years 8 months ago
1998
We describe a new iterative method for parameter estimation of Gaussian mixtures. The new method is based on a framework developed by Kivinen and Warmuth for supervised on-line le...
KDD
2009
ACM
14 years 8 months ago
2009
ACM
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
This work presents GROUSE (Grassmanian Rank-One Update Subspace Estimation), an efficient online algorithm for tracking subspaces from highly incomplete observations. GROUSE requi...
ICANN
2009
Springer
14 years 1 months ago
2009
Springer
The best recent supervised sequence learning methods use gradient descent to train networks of miniature nets called memory cells. The most popular cell structure seems somewhat ar...
JMLR
2012
11 years 9 months ago
2012
We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...