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» An Effective Learning Method for Max-Min Neural Networks
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ITS
2010
Springer
178views Multimedia» more  ITS 2010»
15 years 9 months ago
Learning What Works in ITS from Non-traditional Randomized Controlled Trial Data
The traditional, well established approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pretest and posttest desig...
Zachary A. Pardos, Matthew D. Dailey, Neil T. Heff...
JNCA
2007
136views more  JNCA 2007»
15 years 4 months ago
Adaptive anomaly detection with evolving connectionist systems
Anomaly detection holds great potential for detecting previously unknown attacks. In order to be effective in a practical environment, anomaly detection systems have to be capable...
Yihua Liao, V. Rao Vemuri, Alejandro Pasos
CLUSTER
2007
IEEE
15 years 8 months ago
Identifying energy-efficient concurrency levels using machine learning
Abstract-- Multicore microprocessors have been largely motivated by the diminishing returns in performance and the increased power consumption of single-threaded ILP microprocessor...
Matthew Curtis-Maury, Karan Singh, Sally A. McKee,...
ICMAS
2000
15 years 5 months ago
Assessing Usage Patterns to Improve Data Allocation via Auctions
The data allocation problem in incomplete information environments consisting of self-motivated servers responding to users' queries is considered. Periodically, the servers ...
Rina Azoulay-Schwartz, Sarit Kraus
NN
2000
Springer
159views Neural Networks» more  NN 2000»
15 years 4 months ago
Independent component analysis for noisy data -- MEG data analysis
ICA (independent component analysis) is a new, simple and powerful idea for analyzing multi-variant data. One of the successful applications is neurobiological data analysis such ...
Shiro Ikeda, Keisuke Toyama