701 search results - page 53 / 141 » Self Bounding Learning Algorithms |
NIPS
1998
13 years 11 months ago
1998
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
COLT
2007
Springer
14 years 4 months ago
2007
Springer
We give an algorithm for the on-line learning of permutations. The algorithm maintains its uncertainty about the target permutation as a doubly stochastic weight matrix, and makes...
NIPS
2001
13 years 11 months ago
2001
Greedy approximation algorithms have been frequently used to obtain sparse solutions to learning problems. In this paper, we present a general greedy algorithm for solving a class...
JMLR
2002
13 years 9 months ago
2002
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
ICML
2008
IEEE
14 years 11 months ago
2008
IEEE
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is no...