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» An empirical comparison of supervised learning algorithms
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ICAI
2004
14 years 11 months ago
A Comparison of Resampling Methods for Clustering Ensembles
-- Combination of multiple clusterings is an important task in the area of unsupervised learning. Inspired by the success of supervised bagging algorithms, we propose a resampling ...
Behrouz Minaei-Bidgoli, Alexander P. Topchy, Willi...
AIIA
2007
Springer
14 years 11 months ago
Trip Around the HMPerceptron Algorithm: Empirical Findings and Theoretical Tenets
Abstract. In a recent work we have carried out CarpeDiem, a novel algorithm for the fast evaluation of Supervised Sequential Learning (SSL) classifiers. In this paper we point out...
Roberto Esposito, Daniele P. Radicioni
PAMI
2011
14 years 4 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang
NIPS
2008
14 years 11 months ago
An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis
We study the problem of domain transfer for a supervised classification task in mRNA splicing. We consider a number of recent domain transfer methods from machine learning, includ...
Gabriele Schweikert, Christian Widmer, Bernhard Sc...
ATAL
2009
Springer
15 years 4 months ago
Generalized model learning for reinforcement learning in factored domains
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
Todd Hester, Peter Stone