495 search results - page 55 / 99 » Approximation algorithms for budgeted learning problems |
108
Voted
DIS
2008
Springer
15 years 4 months ago
2008
Springer
Abstract. An important task in many scientific and engineering disciplines is to set up experiments with the goal of finding the best instances (substances, compositions, designs) ...
117
Voted
SODA
2001
ACM
15 years 4 months ago
2001
ACM
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
129
Voted
ICMLA
2009
15 years 10 days ago
2009
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
122
Voted
ML
2002
ACM
15 years 2 months ago
2002
ACM
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
91
Voted
TNN
2008
15 years 2 months ago
2008
In this paper, a general method for the numerical solution of maximum-likelihood estimation (MLE) problems is presented; it adopts the deterministic learning (DL) approach to find ...