70 search results - page 7 / 14 » Bottom-Up Learning of Markov Network Structure |
CORR
2010
Springer
13 years 6 months ago
2010
Springer
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M3 N) is an effective approach. All state-of-...
NIPS
2003
13 years 9 months ago
2003
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
JMLR
2010
13 years 2 months ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
NIPS
1994
13 years 9 months ago
1994
We introduce a recurrent architecture having a modular structure and we formulate a training procedure based on the EM algorithm. The resulting model has similarities to hidden Ma...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
In this paper, we survey the current state-ofart models for structured learning problems, including Hidden Markov Model (HMM), Conditional Random Fields (CRF), Averaged Perceptron...