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ISMB
2000
15 years 8 months ago
A Probabilistic Learning Approach to Whole-Genome Operon Prediction
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...
ICML
2010
IEEE
15 years 7 months ago
Budgeted Nonparametric Learning from Data Streams
We consider the problem of extracting informative exemplars from a data stream. Examples of this problem include exemplarbased clustering and nonparametric inference such as Gauss...
Ryan Gomes, Andreas Krause
IJSNET
2006
145views more  IJSNET 2006»
15 years 6 months ago
RL-MAC: a reinforcement learning based MAC protocol for wireless sensor networks
:This paper introduces RL-MAC, a novel adaptive MediaAccess Control (MAC) protocol for Wireless Sensor Networks (WSN) that employs a reinforcement learning framework. Existing sche...
Zhenzhen Liu, Itamar Elhanany
PAMI
2008
176views more  PAMI 2008»
15 years 6 months ago
Learning Flexible Features for Conditional Random Fields
Abstract-- Extending traditional models for discriminative labeling of structured data to include higher-order structure in the labels results in an undesirable exponential increas...
Liam Stewart, Xuming He, Richard S. Zemel
PRL
2008
91views more  PRL 2008»
15 years 6 months ago
Fuzzy relevance vector machine for learning from unbalanced data and noise
Handing unbalanced data and noise are two important issues in the field of machine learning. This paper proposed a complete framework of fuzzy relevance vector machine by weightin...
Dingfang Li, Wenchao Hu, Wei Xiong, Jin-Bo Yang