3837 search results - page 2 / 768 » Learning Approximate Consistencies |
NIPS
2007
13 years 6 months ago
2007
Clustering is often formulated as a discrete optimization problem. The objective is to find, among all partitions of the data set, the best one according to some quality measure....
ECML
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
STOC
2006
ACM
14 years 5 months ago
2006
ACM
Producing a small DNF expression consistent with given data is a classical problem in computer science that occurs in a number of forms and has numerous applications. We consider ...
FUZZIEEE
2007
IEEE
13 years 11 months ago
2007
IEEE
— Reinforcement learning (RL) is a learning control paradigm that provides well-understood algorithms with good convergence and consistency properties. Unfortunately, these algor...
EMMCVPR
2005
Springer
2005
Springer
Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study
13 years 10 months ago
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...