Relevant bibliographies by topics / Heterogeneous neural networks

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  1. Dissertations / Theses

Academic literature on the topic 'Heterogeneous neural networks'

Author: Grafiati
Published: 6 September 2023

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Dissertations / Theses on the topic "Heterogeneous neural networks"

1

Belanche, Muñoz Lluís A. (Lluís Antoni). "Heterogeneous neural networks: theory and applications." Doctoral thesis, Universitat Politècnica de Catalunya, 2000. http://hdl.handle.net/10803/6660.

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Aquest treball presenta una classe de funcions que serveixen de models neuronals generalitzats per ser usats en xarxes neuronals artificials. Es defineixen com una mesura de similitud que actúa com una definició flexible de neurona vista com un reconeixedor de patrons. <br/>La similitud proporciona una marc conceptual i serveix de cobertura unificadora de molts models neuronals de la literatura i d'exploració de noves instàncies de models de neurona.<br/> <br/>La visió basada en similitud porta amb naturalitat a integrar informació heterogènia, com ara quantitats contínues i discretes (nomina
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2

Belanche, Muñoz Lluis. "Heterogeneous neural networks: theory and applications." Doctoral thesis, Universitat Politècnica de Catalunya, 2000. http://hdl.handle.net/10803/6660.

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Abstract:
Aquest treball presenta una classe de funcions que serveixen de models neuronals generalitzats per ser usats en xarxes neuronals artificials. Es defineixen com una mesura de similitud que actúa com una definició flexible de neurona vista com un reconeixedor de patrons. La similitud proporciona una marc conceptual i serveix de cobertura unificadora de molts models neuronals de la literatura i d'exploració de noves instàncies de models de neurona. La visió basada en similitud porta amb naturalitat a integrar informació heterogènia, com ara quantitats contínues i discretes (nominals i ordinals),
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3

Cabana, Tanguy. "Large deviations for the dynamics of heterogeneous neural networks." Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066551/document.

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Cette thèse porte sur l'obtention rigoureuse de limites de champ moyen pour la dynamique continue de grands réseaux de neurones hétérogènes. Nous considérons des neurones à taux de décharge, et sujets à un bruit Brownien additif. Le réseau est entièrement connecté, avec des poids de connections dont la variance décroît comme l'inverse du nombre de neurones conservant un effet non trivial dans la limite thermodynamique. Un second type d'hétérogénéité, interprété comme une position spatiale, est considéré au niveau de chaque cellule. Pour la pertinence biologique, nos modèles incluent ou bien de
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4

Zhao, Qiwei. "Federated Learning with Heterogeneous Challenge." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/27399.

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Federated learning allows the training of a model from the distributed data of many clients under the orchestration of a central server. With the increasing concern on privacy, federated learning draws great attention from both academia and industry. However, the heterogeneous challenges introduced by natural characters of federated learning settings significantly degrade the performance of federated learning methods. Specifically, these heterogeneous challenges include the heterogeneous data challenges and the heterogeneous scenario challenges. Data heterogeneous challenges mean the signif
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5

Schliebs, Stefan. "Heterogeneous probabilistic models for optimisation and modelling of evolving spiking neural networks." AUT University, 2010. http://hdl.handle.net/10292/963.

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This thesis proposes a novel feature selection and classification method employing evolving spiking neural networks (eSNN) and evolutionary algorithms (EA). The method is named the Quantum-inspired Spiking Neural Network (QiSNN) framework. QiSNN represents an integrated wrapper approach. An evolutionary process evolves appropriate feature subsets for a given classification task and simultaneously optimises the neural and learning-related parameters of the network. Unlike other methods, the connection weights of this network are determined by a fast one-pass learning algorithm which dramaticall
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6

Antoniou, Christos Andrea. "Improving the acoustic modelling of speech using modular/ensemble combinations of heterogeneous neural networks." Thesis, University of Essex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340582.

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7

Wilson, Daniel B. "Combining genetic algorithms and artificial neural networks to select heterogeneous dispatching rules for a job shop system." Ohio : Ohio University, 1996. http://www.ohiolink.edu/etd/view.cgi?ohiou1177701025.

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8

Hobro, Mark. "Semantic Integration across Heterogeneous Databases : Finding Data Correspondences using Agglomerative Hierarchical Clustering and Artificial Neural Networks." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-226657.

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The process of data integration is an important part of the database field when it comes to database migrations and the merging of data. The research in the area has grown with the addition of machine learning approaches in the last 20 years. Due to the complexity of the research field, no go-to solutions have appeared. Instead, a wide variety of ways of enhancing database migrations have emerged. This thesis examines how well a learning-based solution performs for the semantic integration problem in database migrations. Two algorithms are implemented. One that is based on information retrieva
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9

Tekleyohannes, Anteneh Tesfaye. "Unified and heterogeneous modeling of water vapour sorption in Douglas-fir wood with artificial neural networks." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/23032.

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The objective of this study was firstly to investigate and understand sorption properties of earlywood, latewood, annual rings and gross wood. Secondly, to develop a heterogeneous sorption model for earlywood, latewood and annual rings by taking into consideration unified complex interactions of anatomy, chemical composition and thermodynamic parameters. Thirdly, to upscale the annual ring level model to gross wood by applying artificial neural networks (ANNs) modeling tools using dimensionally reduced inputs through dimensional analysis and genetic algorithms. Four novel physical models, na
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10

Toledo, Testa Juan Ignacio. "Information extraction from heterogeneous handwritten documents." Doctoral thesis, Universitat Autònoma de Barcelona, 2019. http://hdl.handle.net/10803/667388.

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L’objectiu d’aquesta tesi és l’extracció d’Informació de documents total o parcialment manuscrits amb una certa estructura. Bàsicament treballem amb dos escenaris d’aplicació diferent. El primer escenari són els documents moderns altament estructurats, com formularis. En aquests documents, la informació semàntica està ja definida en camps, amb una posició concreta al document i l’extracció de la informació és equivalent a una transcripció. El segon escenari son els documents semi-estructurats totalment manuscrits on, a més de transcriure, cal associar un valor semàntic, d’entre un conjunt cone
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