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ALT
2008
Springer
16 years 16 days ago
Exploiting Cluster-Structure to Predict the Labeling of a Graph
Abstract. The nearest neighbor and the perceptron algorithms are intuitively motivated by the aims to exploit the “cluster” and “linear separation” structure of the data to...
Mark Herbster
115
Voted
ALT
2007
Springer
16 years 16 days ago
Learning Rational Stochastic Tree Languages
Abstract. We consider the problem of learning stochastic tree languages, i.e. probability distributions over a set of trees T(F), from a sample of trees independently drawn accordi...
François Denis, Amaury Habrard
124
Voted
ALT
2006
Springer
16 years 16 days ago
Smooth Boosting Using an Information-Based Criterion
Abstract. Smooth boosting algorithms are variants of boosting methods which handle only smooth distributions on the data. They are proved to be noise-tolerant and can be used in th...
Kohei Hatano
128
Voted
ALT
2006
Springer
16 years 16 days ago
Towards a Better Understanding of Incremental Learning
Abstract. The present study aims at insights into the nature of incremental learning in the context of Gold’s model of identification in the limit. With a focus on natural requi...
Sanjay Jain, Steffen Lange, Sandra Zilles
122
Voted
ALT
2006
Springer
16 years 16 days ago
Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice
Abstract. We propose a thresholded ensemble model for ordinal regression problems. The model consists of a weighted ensemble of confidence functions and an ordered vector of thres...
Hsuan-Tien Lin, Ling Li