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ISCC
2006
IEEE
188views Communications» more  ISCC 2006»
16 years 27 days ago
Active Learning Driven Data Acquisition for Sensor Networks
Online monitoring of a physical phenomenon over a geographical area is a popular application of sensor networks. Networks representative of this class of applications are typicall...
Anish Muttreja, Anand Raghunathan, Srivaths Ravi, ...
188
Voted
ECTEL
2007
Springer
16 years 1 months ago
Integration in Generic Tool Learning Design to Support Complex Learning Methodologies
: Current learning modelling languages do not allow formalization of scripts where generic tools are required. This limitation is especially relevant on remote courses when using c...
Luis de la Fuente Valentín
157
Voted
MCS
2004
Springer
16 years 7 days ago
Learn++.MT: A New Approach to Incremental Learning
An ensemble of classifiers based algorithm, Learn++, was recently introduced that is capable of incrementally learning new information from datasets that consecutively become avail...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar
178
Voted
ISMB
1993
15 years 8 months ago
Knowledge-Based Generation of Machine-Learning Experiments: Learning with DNA Crystallography Data
Thoughit has been possible in the past to learn to predict DNAhydration patterns from crystallographic data, there is ambiguity in the choice of training data (both in terms of th...
Dawn M. Cohen, Casimir A. Kulikowski, Helen Berman
168
Voted
ICML
1997
IEEE
16 years 7 months ago
Learning Belief Networks in the Presence of Missing Values and Hidden Variables
In recent years there has been a flurry of works on learning probabilistic belief networks. Current state of the art methods have been shown to be successful for two learning scen...
Nir Friedman