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CVPR
2010
IEEE
14 years 6 months ago
Nonparametric Higher-Order Learning for Interactive Segmentation
In this paper, we deal with a generative model for multi-label, interactive segmentation. To estimate the pixel likelihoods for each label, we propose a new higher-order formulatio...
Tae Hoon Kim (Seoul National University), Kyoung M...
DAGSTUHL
2009
13 years 10 months ago
Statistical Mechanics of On-line Learning
We introduce and discuss the application of statistical physics concepts in the context of on-line machine learning processes. The consideration of typical properties of very large...
Michael Biehl, Nestor Caticha, Peter Riegler
CORR
2008
Springer
112views Education» more  CORR 2008»
13 years 9 months ago
Compact Labelings For Efficient First-Order Model-Checking
We consider graph properties that can be checked from labels, i.e., bit sequences, of logarithmic length attached to vertices. We prove that there exists such a labeling for check...
Bruno Courcelle, Cyril Gavoille, Mamadou Moustapha...
EMNLP
2009
13 years 7 months ago
Active Learning by Labeling Features
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
Gregory Druck, Burr Settles, Andrew McCallum
COLT
2004
Springer
14 years 1 months ago
Minimizing Regret with Label Efficient Prediction
We investigate label efficient prediction, a variant, proposed by Helmbold and Panizza, of the problem of prediction with expert advice. In this variant, the forecaster, after gues...
Nicolò Cesa-Bianchi, Gábor Lugosi, G...