7378 search results - page 1033 / 1476 » Introduction to Machine Learning |
195
click to vote
ICML
2004
IEEE
16 years 7 months ago
2004
IEEE
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
190
click to vote
ICML
2004
IEEE
16 years 7 months ago
2004
IEEE
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
157
click to vote
ICML
2004
IEEE
16 years 7 months ago
2004
IEEE
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...
179
click to vote
ICML
2003
IEEE
16 years 7 months ago
2003
IEEE
We investigate methods for planning in a Markov Decision Process where the cost function is chosen by an adversary after we fix our policy. As a running example, we consider a rob...
141
click to vote
ICML
2003
IEEE
16 years 7 months ago
2003
IEEE
We study a class of overrelaxed bound optimization algorithms, and their relationship to standard bound optimizers, such as ExpectationMaximization, Iterative Scaling, CCCP and No...