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TKDE
2012
226views Formal Methods» more  TKDE 2012»
13 years 8 months ago
DDD: A New Ensemble Approach for Dealing with Concept Drift
—Online learning algorithms often have to operate in the presence of concept drifts. A recent study revealed that different diversity levels in an ensemble of learning machines a...
Leandro L. Minku, Xin Yao
SOCIALCOM
2010
15 years 4 months ago
Learning to Predict Ad Clicks Based on Boosted Collaborative Filtering
This paper addresses the topic of social advertising, which refers to the allocation of ads based on individual user social information and behaviors. As social network services (e...
Teng-Kai Fan, Chia-Hui Chang
ATAL
2005
Springer
15 years 12 months ago
Rapid on-line temporal sequence prediction by an adaptive agent
Robust sequence prediction is an essential component of an intelligent agent acting in a dynamic world. We consider the case of near-future event prediction by an online learning ...
Steven Jensen, Daniel Boley, Maria L. Gini, Paul R...
ICALT
2008
IEEE
16 years 24 days ago
Identifying Learning Styles in Learning Management Systems by Using Indications from Students' Behaviour
Making students aware of their learning styles and presenting them with learning material that incorporates their individual learning styles has potential to make learning easier ...
Sabine Graf, Kinshuk, Tzu-Chien Liu
CORR
2006
Springer
111views Education» more  CORR 2006»
15 years 6 months ago
An associative memory for the on-line recognition and prediction of temporal sequences
This paper presents the design of an associative memory with feedback that is capable of on-line temporal sequence learning. A framework for on-line sequence learning has been prop...
Joy Bose, Stephen B. Furber, Jonathan L. Shapiro