1074 search results - page 64 / 215 » Learning by Experience Networks in Learning Organizations |
96
Voted
ICML
2009
IEEE
16 years 1 months ago
2009
IEEE
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
91
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
134
Voted
ISNN
2004
Springer
15 years 6 months ago
2004
Springer
This paper proposes a novel hierarchical clustering method that can classify given data without specified knowledge of the number of classes. In this method, at each node of a hie...
SYNASC
2005
IEEE
15 years 6 months ago
2005
IEEE
The paper presents a new reinforcement learning mechanism for spiking neural networks. The algorithm is derived for networks of stochastic integrate-and-fire neurons, but it can ...
102
Voted
ICDAR
2009
IEEE
15 years 7 months ago
2009
IEEE
Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, inc...