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KDD
2003
ACM
148views Data Mining» more  KDD 2003»
14 years 8 months ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
ECCV
2008
Springer
14 years 9 months ago
An Incremental Learning Method for Unconstrained Gaze Estimation
Abstract. This paper presents an online learning algorithm for appearancebased gaze estimation that allows free head movement in a casual desktop environment. Our method avoids the...
Yusuke Sugano, Yasuyuki Matsushita, Yoichi Sato, H...
TSMC
2008
164views more  TSMC 2008»
13 years 7 months ago
Bagging and Boosting Negatively Correlated Neural Networks
In this paper, we propose two cooperative ensemble learning algorithms, i.e., NegBagg and NegBoost, for designing neural network (NN) ensembles. The proposed algorithms incremental...
Md. Monirul Islam, Xin Yao, S. M. Shahriar Nirjon,...
ECIR
2006
Springer
13 years 9 months ago
Automatic Document Organization in a P2P Environment
Abstract. This paper describes an efficient method to construct reliable machine learning applications in peer-to-peer (P2P) networks by building ensemble based meta methods. We co...
Stefan Siersdorfer, Sergej Sizov
SOFSEM
2007
Springer
14 years 1 months ago
Incremental Learning of Planning Operators in Stochastic Domains
In this work we assume that there is an agent in an unknown environment (domain). This agent has some predefined actions and it can perceive its current state in the environment c...
Javad Safaei, Gholamreza Ghassem-Sani