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GECCO
2009
Springer
161views Optimization» more  GECCO 2009»
16 years 1 months ago
Are evolutionary rule learning algorithms appropriate for malware detection?
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classiļ...
M. Zubair Shafiq, S. Momina Tabish, Muddassar Faro...
GECCO
2007
Springer
168views Optimization» more  GECCO 2007»
16 years 23 days ago
Empirical analysis of generalization and learning in XCS with gradient descent
We analyze generalization and learning in XCS with gradient descent. At first, we show that the addition of gradient in XCS may slow down learning because it indirectly decreases...
Pier Luca Lanzi, Martin V. Butz, David E. Goldberg
IWCLS
2007
Springer
16 years 22 days ago
On Lookahead and Latent Learning in Simple LCS
Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most c...
Larry Bull
ITICSE
2005
ACM
16 years 5 days ago
Learning styles across the curriculum
Recent research has shown that a student’s learning style – essentially, the way a student approaches and masters new material – can affect student performance in introducto...
A. T. Chamillard, Ricky E. Sward
MIR
2005
ACM
129views Multimedia» more  MIR 2005»
16 years 5 days ago
Tracking concept drifting with an online-optimized incremental learning framework
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Jun Wu, Dayong Ding, Xian-Sheng Hua, Bo Zhang