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MCS
2000
Springer
15 years 7 months ago
Ensemble Methods in Machine Learning
Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a (weighted) vote of their predictions. The original ensembl...
Thomas G. Dietterich
CIARP
2008
Springer
15 years 5 months ago
Feature Selection through Dynamic Mesh Optimization
This paper introduces the Dynamic Mesh Optimization meta-heuristic, which falls under the evolutionary computation techniques. Moreover, we outline its application to the feature s...
Rafael Bello, Amilkar Puris, Rafael Falcón,...
CIARP
2006
Springer
15 years 5 months ago
A Probabilistic Approach to Build 2D Line Based Maps from Laser Scans in Indoor Environments
In this work we consider a mobile robot with a laser range finder. Our goal is to find the best set of lines from the sequence of points given by a laser scan. We propose a probabi...
Leonardo Romero, Carlos Lara
NAACL
2003
15 years 5 months ago
Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment
We address the text-to-text generation problem of sentence-level paraphrasing — a phenomenon distinct from and more difficult than word- or phrase-level paraphrasing. Our appro...
Regina Barzilay, Lillian Lee
NIPS
2003
15 years 5 months ago
Multiple-Instance Learning via Disjunctive Programming Boosting
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
Stuart Andrews, Thomas Hofmann