1062 search results - page 63 / 213 » Sublinear Optimization for Machine Learning |
ICML
2009
IEEE
14 years 9 months ago
2009
IEEE
An anytime algorithm is capable of returning a response to the given task at essentially any time; typically the quality of the response improves as the time increases. Here, we c...
ICML
2009
IEEE
14 years 9 months ago
2009
IEEE
In this paper, we present a robust feature extraction framework based on informationtheoretic learning. Its formulated objective aims at simultaneously maximizing the Renyi's...
ECML
2005
Springer
14 years 2 months ago
2005
Springer
Active selection of good training examples is an important approach to reducing data-collection costs in machine learning; however, most existing methods focus on maximizing classi...
ICML
1994
IEEE
14 years 16 days ago
1994
IEEE
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....
NIPS
2008
13 years 10 months ago
2008
Many popular optimization algorithms, like the Levenberg-Marquardt algorithm (LMA), use heuristic-based "controllers" that modulate the behavior of the optimizer during ...