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JSAC
2010
138views more  JSAC 2010»
13 years 8 months ago
Dynamic conjectures in random access networks using bio-inspired learning
—Inspired by the biological entities’ ability to achieve reciprocity in the course of evolution, this paper considers a conjecture-based distributed learning approach that enab...
Yi Su, Mihaela van der Schaar
ICMLA
2008
13 years 11 months ago
Tumor Targeting for Lung Cancer Radiotherapy Using Machine Learning Techniques
Accurate lung tumor targeting in real time plays a fundamental role in image-guide radiotherapy of lung cancers. Precise tumor targeting is required for both respiratory gating an...
Tong Lin, Laura Cervino, Xiaoli Tang, Nuno Vasconc...
VLSISP
2011
358views Database» more  VLSISP 2011»
13 years 5 months ago
Accelerating Machine-Learning Algorithms on FPGAs using Pattern-Based Decomposition
Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from superlinear increases in ...
Karthik Nagarajan, Brian Holland, Alan D. George, ...
GECCO
2004
Springer
150views Optimization» more  GECCO 2004»
14 years 3 months ago
Parameter Adaptation within Co-adaptive Learning Classifier Systems
The authors propose a co-adaptive approach to controlling parameters for coevolution-based learning classifier systems. By taking advantage of the on-line incremental learning capa...
Chung-Yuan Huang, Chuen-Tsai Sun
ABIALS
2008
Springer
14 years 4 months ago
A Two-Level Model of Anticipation-Based Motor Learning for Whole Body Motion
Abstract. We present a model of motor learning based on a combination of Operational Space Control and Optimal Control. Anticipatory processes are used both in the learning of the ...
Camille Salaün, Vincent Padois, Olivier Sigau...