701 search results - page 53 / 141 » Self Bounding Learning Algorithms |
120
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NIPS
1998
15 years 1 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
15 years 6 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...
121
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NIPS
2001
15 years 1 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...
105
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JMLR
2002
15 years 6 days 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
16 years 1 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...