716 search results - page 79 / 144 » Optimizing Sorting with Machine Learning Algorithms |
100
Voted
ICML
2007
IEEE
16 years 3 months ago
2007
IEEE
The l-bfgs limited-memory quasi-Newton method is the algorithm of choice for optimizing the parameters of large-scale log-linear models with L2 regularization, but it cannot be us...
137
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ALT
2005
Springer
15 years 11 months ago
2005
Springer
This paper shows how universal learning can be achieved with expert advice. To this aim, we specify an experts algorithm with the following characteristics: (a) it uses only feedba...
ICML
2005
IEEE
16 years 3 months ago
2005
IEEE
For Hidden Markov Models (HMMs) with fully connected transition models, the three fundamental problems of evaluating the likelihood of an observation sequence, estimating an optim...
162
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ICML
1995
IEEE
16 years 3 months ago
1995
IEEE
In this paper we introduce Ant-Q, a family of algorithms which present many similarities with Q-learning (Watkins, 1989), and which we apply to the solution of symmetric and asymm...
ICML
2006
IEEE
16 years 3 months ago
2006
IEEE
We derive a robust Euclidean embedding procedure based on semidefinite programming that may be used in place of the popular classical multidimensional scaling (cMDS) algorithm. We...