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INFOCOM
2012
IEEE
13 years 9 months ago
Approximately optimal adaptive learning in opportunistic spectrum access
—In this paper we develop an adaptive learning algorithm which is approximately optimal for an opportunistic spectrum access (OSA) problem with polynomial complexity. In this OSA...
Cem Tekin, Mingyan Liu
SAC
2009
ACM
16 years 1 months ago
Evaluating algorithms that learn from data streams
In the past years, the theory and practice of machine learning and data mining have been focused on static and finite data sets from where learning algorithms generate a static m...
João Gama, Pedro Pereira Rodrigues, Raquel ...
KELSI
2004
Springer
16 years 5 days ago
Multiple-Instance Case-Based Learning for Predictive Toxicology
Predictive toxicology is the task of building models capable of determining, with a certain degree of accuracy, the toxicity of chemical compounds. Machine Learning (ML) in general...
Eva Armengol, Enric Plaza
ICMLA
2008
15 years 8 months ago
Target Selection: A New Learning Paradigm and Its Application to Genetic Association Studies
In this work, a new learning paradigm called target selection is proposed, which can be used to test for associations between a single genetic variable and a multidimensional, qua...
Johannes Mohr, Sambu Seo, Imke Puis, Andreas Heinz...
ALT
2004
Springer
16 years 3 months ago
Learning Languages from Positive Data and Negative Counterexamples
In this paper we introduce a paradigm for learning in the limit of potentially infinite languages from all positive data and negative counterexamples provided in response to the ...
Sanjay Jain, Efim B. Kinber