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FOIKS
2008
Springer
14 years 5 months ago
Cost-minimising strategies for data labelling : optimal stopping and active learning
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Christos Dimitrakakis, Christian Savu-Krohn
ACL
2007
13 years 10 months ago
A Comparative Study of Parameter Estimation Methods for Statistical Natural Language Processing
This paper presents a comparative study of five parameter estimation algorithms on four NLP tasks. Three of the five algorithms are well-known in the computational linguistics com...
Jianfeng Gao, Galen Andrew, Mark Johnson, Kristina...
ICML
2010
IEEE
13 years 10 months ago
Particle Filtered MCMC-MLE with Connections to Contrastive Divergence
Learning undirected graphical models such as Markov random fields is an important machine learning task with applications in many domains. Since it is usually intractable to learn...
Arthur Asuncion, Qiang Liu, Alexander T. Ihler, Pa...
TCS
2008
13 years 8 months ago
Learning recursive functions: A survey
Studying the learnability of classes of recursive functions has attracted considerable interest for at least four decades. Starting with Gold's (1967) model of learning in th...
Thomas Zeugmann, Sandra Zilles
PAMI
2002
108views more  PAMI 2002»
13 years 8 months ago
Approximate Bayes Factors for Image Segmentation: The Pseudolikelihood Information Criterion (PLIC)
We propose a method for choosing the number of colors or true gray levels in an image; this allows fully automatic segmentation of images. Our underlying probability model is a hid...
Derek C. Stanford, Adrian E. Raftery