Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Burles, Nathan"'
Autor:
Burles, Nathan
The human brain is extremely effective at performing pattern recognition, even in the presence of noisy or distorted inputs. Artificial neural networks attempt to imitate the structure of the brain, often with a view to mimicking its success. The bin
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.631476
Autor:
Swan, Jeremiah, Burles, Nathan John
Publikováno v:
39th CREST Open Workshop: Measuring, Testing and Optimising Computational Energy Consumption
Scalability remains an issue for program synthesis: - We don’t yet know how to generate sizeable algorithms from scratch. - Generative approaches such as GP still work best at the scale of expressions (though some recent promising results). - Forma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::8552ca1871e1205b259e5e09bce9d13e
https://eprints.whiterose.ac.uk/88239/1/hyper_quicksort_energy_efficient_sorting_via_the_templar_framework_for_template_method_hyper_heuristics.pdf
https://eprints.whiterose.ac.uk/88239/1/hyper_quicksort_energy_efficient_sorting_via_the_templar_framework_for_template_method_hyper_heuristics.pdf
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
This paper describes an improvement to the Cellular Associative Neural Network, an architecture based on the distributed model of a cellular automaton, allowing it to perform scale invariant pattern matching. The use of tensor products and superposit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::e40036241980df50b5bd4601124f2418
https://eprints.whiterose.ac.uk/88232/1/incorporating_scale_invariance_into_the_cellular_associative_neural_network.pdf
https://eprints.whiterose.ac.uk/88232/1/incorporating_scale_invariance_into_the_cellular_associative_neural_network.pdf
Autor:
Burles, Nathan John
The human brain is extremely effective at performing pattern recognition, even in the presence of noisy or distorted inputs. Artificial neural networks attempt to imitate the structure of the brain, often with a view to mimicking its success. The bin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::f38ab5246efaccf377fc37ede3fabf4f
https://eprints.whiterose.ac.uk/88238/1/Pattern_Recognition_Using_Associative_Memories.pdf
https://eprints.whiterose.ac.uk/88238/1/Pattern_Recognition_Using_Associative_Memories.pdf
Despite their relative simplicity, Correlation Matrix Memories (CMMs) are an active area of research, as they are able to be integrated into more complex architectures such as the Associative Rule Chaining Architecture (ARCA) [1]. In this architectur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::52f0073331548a90ba4b145be5d29bdd
https://eprints.whiterose.ac.uk/75671/1/enamel_final.pdf
https://eprints.whiterose.ac.uk/75671/1/enamel_final.pdf
Publikováno v:
Artificial Neural Networks and Machine Learning-ICANN 2013
This paper describes improvements to the rule chaining architecture presented in [1]. The architecture uses distributed associative memories to allow the system to utilise memory eciently, and superimposed distributed representations in order to redu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::3fe52f95f12872a80391c5d8a9aae428
https://eprints.whiterose.ac.uk/75674/1/improvingTheAssociativeRuleChainingArchitecture_final.pdf
https://eprints.whiterose.ac.uk/75674/1/improvingTheAssociativeRuleChainingArchitecture_final.pdf
Publikováno v:
Artificial Neural Networks and Machine Learning – ICANN 2012
This paper describes an architecture based on superimposed distributed representations and distributed associative memories which is capable of performing rule chaining. The use of a distributed representation allows the system to utilise memory effi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::3e1c67eb4645332f1604815439e8f94d
https://eprints.whiterose.ac.uk/88231/1/ruleChainingSystem.pdf
https://eprints.whiterose.ac.uk/88231/1/ruleChainingSystem.pdf
Publikováno v:
GECCO 2011, GPUs for Genetic and Evolutionary Computation Competition
We submit an implementation of an Estimation of Distribution Algorithm – specifically a variant of the Bayesian Optimisation Algorithm (BOA) – using GPGPU. Every aspect of the algorithm is executed on the device, and it makes effective of use mul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::cd2e9496fb3307987d13446e1c0e68f5
https://eprints.whiterose.ac.uk/88233/1/edaIsingSpinGlass.pdf
https://eprints.whiterose.ac.uk/88233/1/edaIsingSpinGlass.pdf
Autor:
Burles, Nathan John
Correlation matrix memories have been successfully applied to many domains. This work implements a production system put forward in [Austin, 2003], to demonstrate its viability as an efficient rule-chaining process. Background information on rule-cha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::4dd13f0ac11dc399caee55521d532557
https://eprints.whiterose.ac.uk/88236/1/quantum_parallel_computation_with_neural_networks.pdf
https://eprints.whiterose.ac.uk/88236/1/quantum_parallel_computation_with_neural_networks.pdf