Artigos de revistas sobre o tema "Non-parametric learning"
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Liu, Bing, Shi-Xiong Xia e Yong Zhou. "Unsupervised non-parametric kernel learning algorithm". Knowledge-Based Systems 44 (maio de 2013): 1–9. http://dx.doi.org/10.1016/j.knosys.2012.12.008.
Texto completo da fonteEsser, Pascal, Maximilian Fleissner e Debarghya Ghoshdastidar. "Non-parametric Representation Learning with Kernels". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 11 (24 de março de 2024): 11910–18. http://dx.doi.org/10.1609/aaai.v38i11.29077.
Texto completo da fonteCruz, David Luviano, Francesco José García Luna e Luis Asunción Pérez Domínguez. "Multiagent reinforcement learning using Non-Parametric Approximation". Respuestas 23, n.º 2 (1 de julho de 2018): 53–61. http://dx.doi.org/10.22463/0122820x.1738.
Texto completo da fonteKhadse, Vijay M., Parikshit Narendra Mahalle e Gitanjali R. Shinde. "Statistical Study of Machine Learning Algorithms Using Parametric and Non-Parametric Tests". International Journal of Ambient Computing and Intelligence 11, n.º 3 (julho de 2020): 80–105. http://dx.doi.org/10.4018/ijaci.2020070105.
Texto completo da fonteYoa, Seungdong, Jinyoung Park e Hyunwoo J. Kim. "Learning Non-Parametric Surrogate Losses With Correlated Gradients". IEEE Access 9 (2021): 141199–209. http://dx.doi.org/10.1109/access.2021.3120092.
Texto completo da fonteRutkowski, Leszek. "Non-parametric learning algorithms in time-varying environments". Signal Processing 18, n.º 2 (outubro de 1989): 129–37. http://dx.doi.org/10.1016/0165-1684(89)90045-5.
Texto completo da fonteLiu, Mingming, Bing Liu, Chen Zhang e Wei Sun. "Embedded non-parametric kernel learning for kernel clustering". Multidimensional Systems and Signal Processing 28, n.º 4 (10 de agosto de 2016): 1697–715. http://dx.doi.org/10.1007/s11045-016-0440-1.
Texto completo da fonteChen, Changyou, Junping Zhang, Xuefang He e Zhi-Hua Zhou. "Non-Parametric Kernel Learning with robust pairwise constraints". International Journal of Machine Learning and Cybernetics 3, n.º 2 (17 de setembro de 2011): 83–96. http://dx.doi.org/10.1007/s13042-011-0048-6.
Texto completo da fonteKaur, Navdeep, Gautam Kunapuli e Sriraam Natarajan. "Non-parametric learning of lifted Restricted Boltzmann Machines". International Journal of Approximate Reasoning 120 (maio de 2020): 33–47. http://dx.doi.org/10.1016/j.ijar.2020.01.003.
Texto completo da fonteWang, Mingyang, Zhenshan Bing, Xiangtong Yao, Shuai Wang, Huang Kai, Hang Su, Chenguang Yang e Alois Knoll. "Meta-Reinforcement Learning Based on Self-Supervised Task Representation Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 8 (26 de junho de 2023): 10157–65. http://dx.doi.org/10.1609/aaai.v37i8.26210.
Texto completo da fonteJung, Hyungjoo, e Kwanghoon Sohn. "Single Image Depth Estimation With Integration of Parametric Learning and Non-Parametric Sampling". Journal of Korea Multimedia Society 19, n.º 9 (30 de setembro de 2016): 1659–68. http://dx.doi.org/10.9717/kmms.2016.19.9.1659.
Texto completo da fonteTanwani, Ajay Kumar, e Sylvain Calinon. "Small-variance asymptotics for non-parametric online robot learning". International Journal of Robotics Research 38, n.º 1 (11 de dezembro de 2018): 3–22. http://dx.doi.org/10.1177/0278364918816374.
Texto completo da fonteZHANG, Chao, e Takuya AKASHI. "Two-Side Agreement Learning for Non-Parametric Template Matching". IEICE Transactions on Information and Systems E100.D, n.º 1 (2017): 140–49. http://dx.doi.org/10.1587/transinf.2016edp7233.
Texto completo da fonteMa, Yuchao, e Hassan Ghasemzadeh. "LabelForest: Non-Parametric Semi-Supervised Learning for Activity Recognition". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julho de 2019): 4520–27. http://dx.doi.org/10.1609/aaai.v33i01.33014520.
Texto completo da fontePareek, Parikshit, Chuan Wang e Hung D. Nguyen. "Non-parametric probabilistic load flow using Gaussian process learning". Physica D: Nonlinear Phenomena 424 (outubro de 2021): 132941. http://dx.doi.org/10.1016/j.physd.2021.132941.
Texto completo da fonteNaeem, Muhammad, e Sohail Asghar. "Structure learning via non-parametric factorized joint likelihood function". Journal of Intelligent & Fuzzy Systems 27, n.º 3 (2014): 1589–99. http://dx.doi.org/10.3233/ifs-141125.
Texto completo da fonteKarumanchi, Sisir, Thomas Allen, Tim Bailey e Steve Scheding. "Non-parametric Learning to Aid Path Planning over Slopes". International Journal of Robotics Research 29, n.º 8 (4 de maio de 2010): 997–1018. http://dx.doi.org/10.1177/0278364910370241.
Texto completo da fonteDervilis, Nikolaos, Thomas E. Simpson, David J. Wagg e Keith Worden. "Nonlinear modal analysis via non-parametric machine learning tools". Strain 55, n.º 1 (15 de outubro de 2018): e12297. http://dx.doi.org/10.1111/str.12297.
Texto completo da fonteBarut, Emre, e Warren B. Powell. "Optimal learning for sequential sampling with non-parametric beliefs". Journal of Global Optimization 58, n.º 3 (3 de março de 2013): 517–43. http://dx.doi.org/10.1007/s10898-013-0050-5.
Texto completo da fonteLu, Zhong-Lin, Yukai Zhao, Jiajuan Liu e Barbara Dosher. "Non-parametric Hierarchical Bayesian Modeling of the Learning Curve in Perceptual Learning". Journal of Vision 23, n.º 9 (1 de agosto de 2023): 5752. http://dx.doi.org/10.1167/jov.23.9.5752.
Texto completo da fonteGaviria-Chavarro, Javier, Isabel Cristina Rojas-Padilla e Yury Vergara-López. "Virtual Learning Object (VLO) for Teaching and Learning Non-Parametric Statistical Methods". Tecné, Episteme y Didaxis: TED, n.º 54 (1 de julho de 2023): 285–302. http://dx.doi.org/10.17227/ted.num54-14155.
Texto completo da fonteDeco, Gustavo, Ralph Neuneier e Bernd Schümann. "Non-parametric Data Selection for Neural Learning in Non-stationary Time Series". Neural Networks 10, n.º 3 (abril de 1997): 401–7. http://dx.doi.org/10.1016/s0893-6080(96)00108-6.
Texto completo da fontePal, Dipan K., e Marios Savvides. "Non-Parametric Transformation Networks for Learning General Invariances from Data". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julho de 2019): 4667–74. http://dx.doi.org/10.1609/aaai.v33i01.33014667.
Texto completo da fonteKardan, Ahmad Agha, e Samira Ghareh Gozlou. "A new non-parametric feature learning for supervised link prediction". International Journal of System Control and Information Processing 1, n.º 4 (2015): 319. http://dx.doi.org/10.1504/ijscip.2015.075877.
Texto completo da fonteYang, Z., e C. W. Chan. "Learning control for non-parametric uncertainties with new convergence property". IET Control Theory & Applications 4, n.º 10 (1 de outubro de 2010): 2177–83. http://dx.doi.org/10.1049/iet-cta.2009.0458.
Texto completo da fonteWang, Yi, Bin Li, Yang Wang, Fang Chen, Bang Zhang e Zhidong Li. "Robust Bayesian non-parametric dictionary learning with heterogeneous Gaussian noise". Computer Vision and Image Understanding 150 (setembro de 2016): 31–43. http://dx.doi.org/10.1016/j.cviu.2016.05.015.
Texto completo da fonteLi, Der-Chang, e Chun-Wu Yeh. "A non-parametric learning algorithm for small manufacturing data sets". Expert Systems with Applications 34, n.º 1 (janeiro de 2008): 391–98. http://dx.doi.org/10.1016/j.eswa.2006.09.008.
Texto completo da fontePark, Yeonseok, Anthony Choi e Keonwook Kim. "Parametric Estimations Based on Homomorphic Deconvolution for Time of Flight in Sound Source Localization System". Sensors 20, n.º 3 (10 de fevereiro de 2020): 925. http://dx.doi.org/10.3390/s20030925.
Texto completo da fonteSouaissi, Zina, Taha B. M. J. Ouarda e André St-Hilaire. "Non-parametric, semi-parametric, and machine learning models for river temperature frequency analysis at ungauged basins". Ecological Informatics 75 (julho de 2023): 102107. http://dx.doi.org/10.1016/j.ecoinf.2023.102107.
Texto completo da fonteMaddalena, Emilio T., e Colin N. Jones. "Learning Non-Parametric Models with Guarantees: A Smooth Lipschitz Regression Approach". IFAC-PapersOnLine 53, n.º 2 (2020): 965–70. http://dx.doi.org/10.1016/j.ifacol.2020.12.1265.
Texto completo da fonteWang, Dongqi, Haoran Wei, Zhirui Zhang, Shujian Huang, Jun Xie e Jiajun Chen. "Non-parametric Online Learning from Human Feedback for Neural Machine Translation". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 10 (28 de junho de 2022): 11431–39. http://dx.doi.org/10.1609/aaai.v36i10.21395.
Texto completo da fonteTohill, C., L. Ferreira, C. J. Conselice, S. P. Bamford e F. Ferrari. "Quantifying Non-parametric Structure of High-redshift Galaxies with Deep Learning". Astrophysical Journal 916, n.º 1 (1 de julho de 2021): 4. http://dx.doi.org/10.3847/1538-4357/ac033c.
Texto completo da fonteWirayasa, I. Ketut Adi, Arko Djajadi, H. Andri Santoso e Eko Indrajit. "Comparison Non-Parametric Machine Learning Algorithms for Prediction of Employee Talent". IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 15, n.º 4 (31 de outubro de 2021): 403. http://dx.doi.org/10.22146/ijccs.69366.
Texto completo da fonteSingh, Sumeet, Jonathan Lacotte, Anirudha Majumdar e Marco Pavone. "Risk-sensitive inverse reinforcement learning via semi- and non-parametric methods". International Journal of Robotics Research 37, n.º 13-14 (22 de maio de 2018): 1713–40. http://dx.doi.org/10.1177/0278364918772017.
Texto completo da fonteSyed, Zeeshan, Ilan Rubinfeld, Pat Patton, Jennifer Ritz, Jack Jordan, Andrea Doud e Vic Velanovich. "Using diagnostic codes for risk adjustment: A non-parametric learning approach". Journal of the American College of Surgeons 211, n.º 3 (setembro de 2010): S99—S100. http://dx.doi.org/10.1016/j.jamcollsurg.2010.06.262.
Texto completo da fonteNesa, Nashreen, Tania Ghosh e Indrajit Banerjee. "Non-parametric sequence-based learning approach for outlier detection in IoT". Future Generation Computer Systems 82 (maio de 2018): 412–21. http://dx.doi.org/10.1016/j.future.2017.11.021.
Texto completo da fonteNurul Amelina Nasharuddin e Nurul Shuhada Zamri. "Non-Parametric Machine Learning for Pollinator Image Classification: A Comparative Study". Journal of Advanced Research in Applied Sciences and Engineering Technology 34, n.º 1 (23 de novembro de 2023): 106–15. http://dx.doi.org/10.37934/araset.34.1.106115.
Texto completo da fonteHerranz-Matey, Ivan, e Luis Ruiz-Garcia. "New Agricultural Tractor Manufacturer’s Suggested Retail Price (MSRP) Model in Europe". Agriculture 14, n.º 3 (21 de fevereiro de 2024): 342. http://dx.doi.org/10.3390/agriculture14030342.
Texto completo da fonteHakim, Abdul, Nurhikmah H. Nurhikmah, Nur Halisa, Farida Febriati, Latri Aras e Lutfi B. Lutfi. "The Effect of Online Learning on Student Learning Outcomes in Indonesian Subjects". Journal of Innovation in Educational and Cultural Research 4, n.º 1 (21 de janeiro de 2023): 133–40. http://dx.doi.org/10.46843/jiecr.v4i1.312.
Texto completo da fonteShi, Chao, e Yu Wang. "Non-parametric machine learning methods for interpolation of spatially varying non-stationary and non-Gaussian geotechnical properties". Geoscience Frontiers 12, n.º 1 (janeiro de 2021): 339–50. http://dx.doi.org/10.1016/j.gsf.2020.01.011.
Texto completo da fonteYang, Z., e C. W. Chan. "Conditional iterative learning control for non-linear systems with non-parametric uncertainties under alignment condition". IET Control Theory & Applications 3, n.º 11 (1 de novembro de 2009): 1521–27. http://dx.doi.org/10.1049/iet-cta.2008.0532.
Texto completo da fonteHuang, Lei, Yuqing Ma e Xianglong Liu. "A general non-parametric active learning framework for classification on multiple manifolds". Pattern Recognition Letters 130 (fevereiro de 2020): 250–58. http://dx.doi.org/10.1016/j.patrec.2019.01.013.
Texto completo da fonteShah, Sonali Rajesh, Abhishek Kaushik, Shubham Sharma e Janice Shah. "Opinion-Mining on Marglish and Devanagari Comments of YouTube Cookery Channels Using Parametric and Non-Parametric Learning Models". Big Data and Cognitive Computing 4, n.º 1 (17 de março de 2020): 3. http://dx.doi.org/10.3390/bdcc4010003.
Texto completo da fonteAvramidis, Athanassios N., e Arnoud V. den Boer. "Dynamic pricing with finite price sets: a non-parametric approach". Mathematical Methods of Operations Research 94, n.º 1 (28 de junho de 2021): 1–34. http://dx.doi.org/10.1007/s00186-021-00744-y.
Texto completo da fonteLi, Wei-Ming, e Shi-Ju Ran. "Non-Parametric Semi-Supervised Learning in Many-Body Hilbert Space with Rescaled Logarithmic Fidelity". Mathematics 10, n.º 6 (15 de março de 2022): 940. http://dx.doi.org/10.3390/math10060940.
Texto completo da fonteLasserre, Marvin, Régis Lebrun e Pierre-Henri Wuillemin. "Learning Continuous High-Dimensional Models using Mutual Information and Copula Bayesian Networks". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 13 (18 de maio de 2021): 12139–46. http://dx.doi.org/10.1609/aaai.v35i13.17441.
Texto completo da fonteGuo, Longwei, Hao Zhu, Yuanxun Lu, Menghua Wu e Xun Cao. "RAFaRe: Learning Robust and Accurate Non-parametric 3D Face Reconstruction from Pseudo 2D&3D Pairs". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 1 (26 de junho de 2023): 719–27. http://dx.doi.org/10.1609/aaai.v37i1.25149.
Texto completo da fontePark, Yeonseok, Anthony Choi e Keonwook Kim. "Single-Channel Multiple-Receiver Sound Source Localization System with Homomorphic Deconvolution and Linear Regression". Sensors 21, n.º 3 (23 de janeiro de 2021): 760. http://dx.doi.org/10.3390/s21030760.
Texto completo da fonteLong, Alexander, Alan Blair e Herke van Hoof. "Fast and Data Efficient Reinforcement Learning from Pixels via Non-parametric Value Approximation". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 7 (28 de junho de 2022): 7620–27. http://dx.doi.org/10.1609/aaai.v36i7.20728.
Texto completo da fonteLee, SiHun, Kijoo Jang, Haeseong Cho, Haedong Kim e SangJoon Shin. "Parametric non-intrusive model order reduction for flow-fields using unsupervised machine learning". Computer Methods in Applied Mechanics and Engineering 384 (outubro de 2021): 113999. http://dx.doi.org/10.1016/j.cma.2021.113999.
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