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KDD
2002
ACM
157views Data Mining» more  KDD 2002»
15 years 10 months ago
Exploiting unlabeled data in ensemble methods
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Kristin P. Bennett, Ayhan Demiriz, Richard Maclin
IJCNN
2007
IEEE
15 years 4 months ago
Two-stage Multi-class AdaBoost for Facial Expression Recognition
— Although AdaBoost has achieved great success, it still suffers from following problems: (1) the training process could be unmanageable when the number of features is extremely ...
Hongbo Deng, Jianke Zhu, Michael R. Lyu, Irwin Kin...
IEAAIE
2005
Springer
15 years 3 months ago
Movement Prediction from Real-World Images Using a Liquid State Machine
Prediction is an important task in robot motor control where it is used to gain feedback for a controller. With such a self-generated feedback, which is available before sensor rea...
Harald Burgsteiner, Mark Kröll, Alexander Leo...
CDC
2010
IEEE
196views Control Systems» more  CDC 2010»
14 years 4 months ago
Convergence and convergence rate of stochastic gradient search in the case of multiple and non-isolated extrema
The asymptotic behavior of stochastic gradient algorithms is studied. Relying on some results of differential geometry (Lojasiewicz gradient inequality), the almost sure pointconve...
Vladislav B. Tadic
CADE
2006
Springer
15 years 10 months ago
Inferring Network Invariants Automatically
Abstract. Verification by network invariants is a heuristic to solve uniform verification of parameterized systems. Given a system P, a network invariant for P is that abstracts th...
Olga Grinchtein, Martin Leucker, Nir Piterman