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» Requirements for Machine Lifelong Learning
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145
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ICDM
2006
IEEE
119views Data Mining» more  ICDM 2006»
15 years 9 months ago
Fast On-line Kernel Learning for Trees
Kernel methods have been shown to be very effective for applications requiring the modeling of structured objects. However kernels for structures usually are too computational dem...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
116
Voted
IWANN
2005
Springer
15 years 9 months ago
Co-evolutionary Learning in Liquid Architectures
A large class of problems requires real-time processing of complex temporal inputs in real-time. These are difficult tasks for state-of-the-art techniques, since they require captu...
Igal Raichelgauz, Karina Odinaev, Yehoshua Y. Zeev...
127
Voted
EUROGP
2003
Springer
15 years 9 months ago
Evolving Finite State Transducers: Some Initial Explorations
Finite state transducers (FSTs) are finite state machines that map strings in a source domain into strings in a target domain. While there are many reports in the literature of ev...
Simon M. Lucas
128
Voted
JMLR
2008
133views more  JMLR 2008»
15 years 3 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
119
Voted
TKDE
2010
168views more  TKDE 2010»
15 years 2 months ago
Completely Lazy Learning
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, San...