An Alternative Objective Function for Markovian Fields

Citation:

S. Kakade, Y. W. Teh, and S. Roweis, An Alternative Objective Function for Markovian Fields. Proceedings of the Nineteenth International Conference on Machine Learning: , 2002.

Abstract:

In labelling or prediction tasks, a trained model's test performance is often based on the quality of its single-time marginal distributions over labels rather than its joint distribution over label sequences. We propose using a new cost function for discriminative learning that more accurately reflects such test time conditions. We present an efficient method to compute the gradient of this cost for Maximum Entropy Markov Models, Conditional Random Fields, and for an extension of these models...

See also: 2002
Last updated on 10/15/2021