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KDD
2009
ACM
224views Data Mining» more  KDD 2009»
14 years 29 days ago
Issues in evaluation of stream learning algorithms
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
João Gama, Raquel Sebastião, Pedro P...
VEE
2012
ACM
269views Virtualization» more  VEE 2012»
12 years 4 months ago
SimTester: a controllable and observable testing framework for embedded systems
In software for embedded systems, the frequent use of interrupts for timing, sensing, and I/O processing can cause concurrency faults to occur due to interactions between applicat...
Tingting Yu, Witawas Srisa-an, Gregg Rothermel
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
13 years 9 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...
GLOBECOM
2009
IEEE
13 years 11 months ago
Compressed Sensing Reception of Bursty UWB Impulse Radio is Robust to Narrow-Band Interference
—We have recently proposed a novel receiver for Ultra-Wide-band Impulse-Radio communication in bursty applications like Wireless Sensor Networks. The receiver, based on the princ...
Anand Oka, Lutz H.-J. Lampe
GECCO
2006
Springer
143views Optimization» more  GECCO 2006»
14 years 1 days ago
DECA: dimension extracting coevolutionary algorithm
Coevolution has often been based on averaged outcomes, resulting in unstable evaluation. Several theoretical approaches have used archives to provide stable evaluation. However, t...
Edwin D. de Jong, Anthony Bucci