Nathan Burles
Nathan Burles
Research Associate in Computer Science, University of York
Bestätigte E-Mail-Adresse bei york.ac.uk
Titel
Zitiert von
Zitiert von
Jahr
Object-oriented genetic improvement for improved energy consumption in Google Guava
N Burles, E Bowles, AEI Brownlee, ZA Kocsis, J Swan, N Veerapen
International Symposium on Search Based Software Engineering, 255-261, 2015
232015
Templar – A Framework for Template-Method Hyper-Heuristics
J Swan, N Burles
European Conference on Genetic Programming, 205-216, 2015
232015
Embedded dynamic improvement
N Burles, J Swan, E Bowles, AEI Brownlee, ZA Kocsis, N Veerapen
Proceedings of the Companion Publication of the 2015 Annual Conference on …, 2015
132015
Search-based energy optimization of some ubiquitous algorithms
AEI Brownlee, N Burles, J Swan
IEEE Transactions on Emerging Topics in Computational Intelligence 1 (3 …, 2017
92017
Specialising Guava’s cache to reduce energy consumption
N Burles, E Bowles, BR Bruce, K Srivisut
International Symposium on Search Based Software Engineering, 276-281, 2015
82015
A rule chaining architecture using a correlation matrix memory
J Austin, S Hobson, N Burles, S O’Keefe
International conference on artificial neural networks, 49-56, 2012
62012
Pattern recognition using associative memories
NJ Burles
42014
‘Quantum’ Parallel computation with neural networks
N Burles
Master’s thesis, University of York, 2010
42010
Extending the Associative Rule Chaining Architecture for Multiple Arity Rules
N Burles, J Austin, S O’Keefe
Neural-Symbolic Learning and Reasoning Workshop at IJCAI 2013, 2013
22013
Improving the Associative Rule Chaining Architecture
N Burles, S O’Keefe, J Austin
Artificial Neural Networks and Machine Learning–ICANN 2013, 98-105, 2013
22013
Incorporating scale invariance into the cellular associative neural network
N Burles, S O’Keefe, J Austin
International Conference on Artificial Neural Networks, 435-442, 2014
12014
ENAMeL: A language for binary correlation matrix memories
N Burles, S O’Keefe, J Austin, S Hobson
Neural processing letters 40 (1), 1-23, 2014
12014
Full Implementation of an Estimation of Distribution Algorithm on a GPU
S Poulding, J Staunton, N Burles
CIGPU Competition, GECCO 2011, 2011
12011
Datasets for the paper" Search-based energy optimization of some ubiquitous algorithms"
AEI Brownlee, N Burles, J Swan
University of Stirling, 2017
2017
Hyper-quicksort: energy efficient sorting via the Templar framework for Template Method Hyper-heuristics
J Swan, NJ Burles
39th CREST Open Workshop: Measuring, Testing and Optimising Computational …, 2015
2015
2017 Index IEEE Transactions on Emerging Topics in Computational Intelligence Vol.
HA Abbass, M Abouhawwash, N Agrawal, A Al-Mamun, C Alippi, V Bajaj, ...
Templar-template-method hyper-heuristics
J Swan, N Burles
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