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1Dissertation/ Thesis
المؤلفون: Farguell Matesanz, Enric
المساهمون: University/Department: Universitat Ramon Llull. EALS - Electrònica
Thesis Advisors: efarguell@hotmail.com, Mazzanti Castrillejo, Ferran, Garriga Berga, Carles
المصدر: TDX (Tesis Doctorals en Xarxa)
مصطلحات موضوعية: Artificial Neural Networks, Decimation, Boltzmann Machines, Artificial Intelligence, Redes Neuronales Artificiales, Decimación, Máquinas de Boltzmann, Inteligencia artificial, Xarxes Neuronals Artificials, Decimació, Màquines de Boltzmann, Intel·ligència artificial, Les TIC i la seva gestió
وصف الملف: application/pdf
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2Academic Journal
المصدر: CQD Revista Eletrônica Paulista de Matemática, Vol 10 (2017)
مصطلحات موضوعية: Reconhecimento facial, Detecção de spoofing, Máquinas de Boltzmann restritas, Campos aletórios de Markov, Métodos estocásticos e estatísticos., Mathematics, QA1-939
وصف الملف: electronic resource
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3
المؤلفون: Navas Gómez, Alfonso de Jesús
المساهمون: Giraldo Gallo, José Jairo, Seoane Bartolomé, Beatriz
مصطلحات موضوعية: Sistemas expertos, Computational complexity, Artificial intelligence, Statistical physics of disordered systems, Restricted Boltzmann machines, Complejidad computacional, Machine learning, Monte-Carlo methods, Física estadística de sistemas desordenados, Métodos de Monte-Carlo, Aprendizaje automatizado, Máquinas de Boltzmann restringidas, Inteligencia artificial
وصف الملف: 39 páginas; application/pdf
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4Dissertation/ Thesis
المؤلفون: Navas Gómez, Alfonso de Jesús
المساهمون: Giraldo Gallo, José Jairo, Seoane Bartolomé, Beatriz
مصطلحات موضوعية: Complejidad computacional, Sistemas expertos, Computational complexity, Inteligencia artificial, Aprendizaje automatizado, Física estadística de sistemas desordenados, Máquinas de Boltzmann restringidas, Métodos de Monte-Carlo, Artificial intelligence, Statistical physics of disordered systems, Restricted Boltzmann machines, Monte-Carlo methods, Machine learning
وصف الملف: 39 páginas; application/pdf
Relation: D. H. Ackley, G. E. Hinton, and T. J. Sejnowski. A learning algorithm for boltzmann machines. Cognitive science, 9(1):147–169, 1985.; D. J. Amit and V. Martin-Mayor. Field theory, the renormalization group, and critical phenomena: graphs to computers. World Scientific Publishing Company, 2005.; A. Bakk and J. S. Høye. One-dimensional ising model applied to protein folding. Physica A: Statistical Mechanics and its Applications, 323:504–518, 2003.; H. Ballesteros and V. Martín-Mayor. Test for random number generators: Schwinger-Dyson equations for the ising model. Physical Review E, 58(5):6787, 1998.; S. Behnel, R. Bradshaw, C. Citro, L. Dalcin, D. S. Seljebotn, and K. Smith. Cython: The best of both worlds. Computing in Science & Engineering, 13(2):31–39, 2011.; N. Béreux, A. Decelle, C. Furtlehner, and B. Seoane. Learning a restricted Boltzmann machine using biased Monte Carlo sampling. arXiv preprint arXiv:2206.01310, 2022.; C. M. Bishop. Pattern Recognition and Machine Learning. Springer, New York, 2006.; B. Bravi, J. Tubiana, S. Cocco, R. Monasson, T. Mora, and A. M. Walczak. Rbm-mhc: A semi-supervised machine-learning method for sample-specific prediction of antigen presentation by hla-i alleles. Cell systems, 12(2):195–202, 2021.; L. Brocchieri and S. Karlin. Protein length in eukaryotic and prokaryotic proteomes. Nucleic acids research, 33(10):3390–3400, 2005.; G. Cossu, L. Del Debbio, T. Giani, A. Khamseh, and M. Wilson. Machine learning determination of dynamical parameters: The ising model case. Physical Review B, 100(6):064304, 2019.; A. Decelle. TorchRBM. https://github.com/AurelienDecelle/TorchRBM, 2021. Accessed: 20-07-2022.; A. Decelle and C. Furtlehner. Restricted Boltzmann machine: Recent advances and mean-field theory. Chinese Physics B, 30(4):040202, 2021.; A. Decelle, C. Furtlehner, and B. Seoane. Equilibrium and non-equilibrium regimes in the learning of restricted boltzmann machines. arXiv preprint arXiv:2105.13889, 2021.; A. Fischer and C. Igel. An introduction to restricted boltzmann machines. In Iberoamerican congress on pattern recognition, pages 14–36. Springer, 2012.; M. Harsh, J. Tubiana, S. Cocco, and R. Monasson. ‘place-cell’ emergence and learning of invariant data with restricted boltzmann machines: breaking and dynamical restoration of continuous symmetries in the weight space. Journal of Physics A: Mathematical and Theoretical, 53(17):174002, 2020.; W. K. Hastings. Monte carlo sampling methods using markov chains and their applications. Biometrika, 57(1):97–109, 1953.; T. L. Hill. Generalization of the one-dimensional Ising model applicable to helix transitions in nucleic acids and proteins. The Journal of Chemical Physics, 30(2):383–387, 1959.; G. E. Hinton. Training products of experts by minimizing contrastive divergence. Neural computation, 14(8):1771–1800, 2002.; G. E. Hinton. A practical guide to training restricted Boltzmann machines. In Neural networks: Tricks of the trade, pages 599–619. Springer, 2012.; G. E. Hinton and R. R. Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313(5786):504–507, 2006.; R. D. Hjelm, V. D. Calhoun, R. Salakhutdinov, E. A. Allen, T. Adali, and S. M. Plis. Restricted boltzmann machines for neuroimaging: an application in identifying intrinsic networks. NeuroImage, 96:245–260, 2014.; N. Le Roux and Y. Bengio. Representational power of restricted Boltzmann machines and deep belief networks. Neural computation, 20(6):1631–1649, 2008.; Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11):2278–2324, 1998.; P. Mehta, M. Bukov, C.-H. Wang, A. G. Day, C. Richardson, C. K. Fisher, and D. J. Schwab. A high-bias, low-variance introduction to machine learning for physicists. Physics reports, 810:1–124, 2019.; R. G. Melko, G. Carleo, J. Carrasquilla, and J. I. Cirac. Restricted boltzmann machines in quantum physics. Nature Physics, 15(9):887–892, 2019.; N. Metropolis, A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller, and E. Teller. Equation of state calculations by fast computing machines. The journal of chemical physics, 21(6):1087–1092, 1953.; G. Montúfar. Restricted Boltzmann machines: Introduction and review. In Information Geometry and Its Applications IV, pages 75–115. Springer, 2016.; F. Ricci-Tersenghi. The Bethe approximation for solving the inverse Ising problem: a comparison with other inference methods. Journal of Statistical Mechanics: Theory and Experiment, 2012(08):P08015, 2012.; D. Sherrington and S. Kirkpatrick. Solvable model of a spin-glass. Physical review letters, 35(26):1792, 1975.; D. Silver, T. Hubert, J. Schrittwieser, I. Antonoglou, M. Lai, A. Guez, M. Lanctot, L. Sifre, D. Kumaran, T. Graepel, et al. A general reinforcement learning algorithm that masters chess, shogi, and go through self-play. Science, 362(6419):1140–1144, 2018.; P. Smolensky. Information processing in dynamical systems: Foundations of harmony theory. In D. E. Rumelhart and J. L. McLelland, editors, Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations, chapter 6, pages 194–281. MIT Press, Cambridge, 1986.; T. Tieleman. Training restricted boltzmann machines using approximations to the likelihood gradient. In Proceedings of the 25th international conference on Machine learning, pages 1064–1071, 2008.; J. Tubiana, S. Cocco, and R. Monasson. Learning protein constitutive motifs from sequence data. Elife, 8:e39397, 2019.; G. Van Rossum and F. L. Drake Jr. Python reference manual. Centrum voor Wiskunde en Informatica Amsterdam, 1995.; U. Wolff. Collective Monte Carlo updating for spin systems. Physical Review Letters, 62(4):361, 1989.; B. Yelmen, A. Decelle, L. Ongaro, D. Marnetto, C. Tallec, F. Montinaro, C. Furtlehner, L. Pagani, and F. Jay. Creating artificial human genomes using generative neural networks. PLoS genetics, 17(2):e1009303, 2021.; https://repositorio.unal.edu.co/handle/unal/83483; Universidad Nacional de Colombia; Repositorio Institucional Universidad Nacional de Colombia; https://repositorio.unal.edu.co/
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5
المؤلفون: Roder, Mateus
المساهمون: Universidade Estadual Paulista (Unesp), Papa, João Paulo [UNESP]
المصدر: Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESPمصطلحات موضوعية: Restricted boltzmann machines, Aprendizado em profundidade, Vídeos, Classificação de eventos, Deep learning, Event classification, Máquinas de Boltzmann Restritas
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6Dissertation/ Thesis
المؤلفون: Roder, Mateus
المساهمون: Universidade Estadual Paulista (UNESP)
مصطلحات موضوعية: Aprendizado em profundidade, Máquinas de Boltzmann Restritas, Classificação de eventos, Vídeos, Deep learning, Restricted boltzmann machines, Event classification
Relation: http://hdl.handle.net/11449/204165; 33004153073P2
الاتاحة: http://hdl.handle.net/11449/204165
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7
المؤلفون: Souza, Gustavo Botelho de
المساهمون: Marana, Aparecido Nilceu, Papa, João Paulo
المصدر: Repositório Institucional da UFSCAR
Universidade Federal de São Carlos (UFSCAR)
instacron:UFSCARمصطلحات موضوعية: Biometria, Spoofing, Reconhecimento facial, Deep learning, Redes neurais de convolução, CIENCIA DA COMPUTACAO [CIENCIAS EXATAS E DA TERRA], Computational efficiency, Restricted Boltzmann machines, Máquinas de Boltzmann restritas, Biometrics, Eficiência computacional, Convolutional neural networks, Presentation attacks, Face recognition, Ataques de apresentação, Aprendizado de máquina em profundidade, CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO [CIENCIAS EXATAS E DA TERRA]
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8Dissertation/ Thesis
المؤلفون: Santos, Daniel Felipe Silva [UNESP]
Thesis Advisors: Universidade Estadual Paulista (UNESP), Marana, Aparecido Nilceu [UNESP]
المصدر: Repositório Institucional da UNESPUniversidade Estadual PaulistaUNESP.
مصطلحات موضوعية: Reconhecimento de veículos, Máquinas de Boltzmann profundas, Máquinas de Boltzmann profundas multinomiais, Projeção bilinear, Vehicle recognition, Deep Boltzmann machines, Multinomial deep Boltzmann machines, Bilinear projection
Relation: 600
الاتاحة: http://hdl.handle.net/11449/151478
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9
المؤلفون: Santos, Daniel Felipe Silva [UNESP]
المساهمون: Universidade Estadual Paulista (Unesp), Marana, Aparecido Nilceu [UNESP]
المصدر: Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESPمصطلحات موضوعية: Projeção bilinear, Reconhecimento de veículos, Máquinas de Boltzmann profundas, Multinomial deep Boltzmann machines, Máquinas de Boltzmann profundas multinomiais, Vehicle recognition, Deep Boltzmann machines, Bilinear projection
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10
المؤلفون: González González, Isaac
المساهمون: González, Ana M, Rodríguez, Francisco de Borja, UAM. Departamento de Tecnología Electrónica y de las Comunicaciones, Rodríguez Ortiz, Francisco Borja
المصدر: Biblos-e Archivo. Repositorio Institucional de la UAM
instnameمصطلحات موضوعية: Telecomunicaciones, extractores de características, Mel Frequency Cepstral Coeficients, Máquinas de Boltzmann
وصف الملف: application/pdf
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11Dissertation/ Thesis
المؤلفون: Souza, Gustavo Botelho de
المساهمون: Marana, Aparecido Nilceu, http://lattes.cnpq.br/6027713750942689, Papa, João Paulo, http://lattes.cnpq.br/9039182932747194, http://lattes.cnpq.br/2368834665313763
مصطلحات موضوعية: Ataques de apresentação, Reconhecimento facial, Biometria, Máquinas de Boltzmann restritas, Redes neurais de convolução, Aprendizado de máquina em profundidade, Eficiência computacional, Presentation attacks, Face recognition, Biometrics, Restricted Boltzmann machines, Convolutional neural networks, Deep learning, Computational efficiency, Spoofing, CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO, CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
Relation: SOUZA, Gustavo Botelho de. Detecção de ataques a sistemas de reconhecimento facial utilizando abordagens eficientes de aprendizado de máquina em profundidade. 2019. Tese (Doutorado em Ciência da Computação) – Universidade Federal de São Carlos, São Carlos, 2019. Disponível em: https://repositorio.ufscar.br/handle/ufscar/11609.; https://repositorio.ufscar.br/handle/ufscar/11609
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12Dissertation/ Thesis
المؤلفون: Santos, Daniel Felipe Silva
المساهمون: Universidade Estadual Paulista (UNESP)
مصطلحات موضوعية: Reconhecimento de veículos, Máquinas de Boltzmann profundas, Máquinas de Boltzmann profundas multinomiais, Projeção bilinear, Vehicle recognition, Deep Boltzmann machines, Multinomial deep Boltzmann machines, Bilinear projection
Relation: http://hdl.handle.net/11449/151478; 000891117; 33004153073P2
الاتاحة: http://hdl.handle.net/11449/151478
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13Academic Journal
المؤلفون: FELIPE JOAO PONTES DA CRUZ
المساهمون: RUY LUIZ MILIDIU
مصطلحات موضوعية: [pt] APRENDIZADO DE MAQUINA, [en] MACHINE LEARNING, [pt] FILTRAGEM COLABORATIVA, [en] COLLABORATIVE FILTERING, [pt] SISTEMAS DE RECOMENDACAO, [en] RECOMMENDER SYSTEMS, [pt] MAQUINAS DE BOLTZMANN RESTRITAS
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14Dissertation/ Thesis
المؤلفون: Silva, Luis Alexandre da [UNESP]
Thesis Advisors: Universidade Estadual Paulista (UNESP), Papa, João Paulo [UNESP], Costa, Kelton Augusto Pontara da [UNESP]
المصدر: Repositório Institucional da UNESPUniversidade Estadual PaulistaUNESP.
مصطلحات موضوعية: Aprendizado de características, Anomalias, Redes de computadores, Redes neurais artificiais, Máquinas de Boltzmann restritas, Feature learning, Anomalies, Computer networks, Artificial neural networks, Restricted Boltzmann machines
Relation: 600
الاتاحة: http://hdl.handle.net/11449/144635
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15
المؤلفون: Silva, Luis Alexandre da [UNESP]
المساهمون: Universidade Estadual Paulista (Unesp), Papa, João Paulo [UNESP], Costa, Kelton Augusto Pontara da [UNESP]
المصدر: Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESPمصطلحات موضوعية: Aprendizado de características, Redes neurais artificiais, Restricted Boltzmann machines, Redes de computadores, Máquinas de Boltzmann restritas, Artificial neural networks, Feature learning, Anomalies, Anomalias, Computer networks
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16Dissertation/ Thesis
المؤلفون: Silva, Luis Alexandre da
المساهمون: Universidade Estadual Paulista (UNESP)
مصطلحات موضوعية: Aprendizado de características, Anomalias, Redes de computadores, Redes neurais artificiais, Máquinas de Boltzmann restritas, Feature learning, Anomalies, Computer networks, Artificial neural networks, Restricted Boltzmann machines
Relation: http://hdl.handle.net/11449/144635; 000875639; 33004153073P2
الاتاحة: http://hdl.handle.net/11449/144635