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TNN
2008
181views more  TNN 2008»
15 years 6 months ago
Optimized Approximation Algorithm in Neural Networks Without Overfitting
In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs). The optimized approx...
Yinyin Liu, Janusz A. Starzyk, Zhen Zhu
ACMICEC
2008
ACM
270views ECommerce» more  ACMICEC 2008»
15 years 8 months ago
Adaptive strategies for predicting bidding prices in supply chain management
Supply Chain Management (SCM) involves a number of interrelated activities from negotiating with suppliers to competing for customer orders and scheduling the manufacturing proces...
Yevgeniya Kovalchuk, Maria Fasli
JAIR
2002
163views more  JAIR 2002»
15 years 6 months ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu
JUCS
2010
183views more  JUCS 2010»
15 years 5 months ago
User Context and Personalized Learning: a Federation of Contextualized Attention Metadata
: Nowadays, personalized education is a very hot topic in technology enhanced learning (TEL) research. To support students during their learning process, the first step consists in...
Valentin Butoianu, Philippe Vidal, Katrien Verbert...
CIKM
2008
Springer
15 years 8 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan