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Keyword

parameter learning

Description: The process of estimating or adapting model parameters from data or experience, including in Bayesian networks and neural control systems.
OpenAlex ID: keywords/parameter-learning
Learning Bayesian Networks
2017 · Claude Sammut, Geoffrey I. Webb · Encyclopedia of Machine Learning and Data Mining · 1,424
Self-Paced Learning for Latent Variable Models
2010 · Manish Kumar, Benjamin Packer, et al. · neural information processing systems · 1,185
Factorial Hidden Markov Models
1997 · Zoubin Ghahramani, Michael I. Jordan · Machine Learning · 1,157
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The bayes net toolbox for matlab
2001 · Keelin Murphy · 1,016
Learning Conditional Random Fields for Stereo
2007 · Daniel Scharstein, Chris Pal · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 886
Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications
2011 · Aurelien Decelle, Florent Krzakala, et al. · Physical Review E · 749
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An Introduction to Hidden Markov Models and Bayesian Networks
2001 · ZOUBIN GHAHRAMANI · International Journal of Pattern Recognition and Artificial Intelligence · 702
Bayesian Analysis in Expert Systems
1993 · David J. Spiegelhalter, A. Philip Dawid, et al. · Statistical Science · 690
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word2vec Parameter Learning Explained
2014 · Rong, Xin · arXiv (Cornell University) · 626
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Interactive Image Segmentation Using an Adaptive GMMRF Model
2004 · Andrew Blake, Carsten Rother, et al. · Lecture notes in computer science · 529
Non-Bayesian social learning
2012 · Ali Jadbabaie, Pooya Molavi, et al. · Games and Economic Behavior · 486
Bayesian networks
2009 · Finn V. Jensen · Wiley Interdisciplinary Reviews Computational Statistics · 476
A guide to the literature on learning probabilistic networks from data
1996 · W. Buntine · IEEE Transactions on Knowledge and Data Engineering · 468
Learning structured prediction models
2005 · Ben Taskar, Vassil Chatalbashev, et al. · International Conference on Machine Learning · 444
Differentiable Learning of Logical Rules for Knowledge Base Reasoning
2017 · Yang, Fan, Yang, Zhilin, et al. · arXiv (Cornell University) · 410
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Accurate model of liquid–liquid phase behavior of intrinsically disordered proteins from optimization of single-chain properties
2021 · Giulio Tesei, Thea K. Schulze, et al. · Proceedings of the National Academy of Sciences · 406
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Learning on Bayesian Networks
2002 · Alexandra A. Vagis · Journal of Automation and Information Sciences · 404
Inference and Phase Transitions in the Detection of Modules in Sparse Networks
2011 · Aurelien Decelle, Florent Krzakala, et al. · Physical Review Letters · 392
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A proposal on reasoning methods in fuzzy rule-based classification systems
1999 · Oscar Cordón, María José del Jesus, et al. · International Journal of Approximate Reasoning · 389
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Learning Belief Networks in the Presence of Missing Values and Hidden Variables
1997 · Nir Friedman · 387
Adaptive Probabilistic Networks with Hidden Variables
1997 · John Binder, Daphne Koller, et al. · Machine Learning · 377
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A computational learning model for metrical phonology
1990 · B.Elan Dresher, Jonathan D. Kaye · Cognition · 353
Learning Bayesian network classifiers by maximizing conditional likelihood
2004 · Daniel Grossman, Pedro Domingos · 308
Reinforcement structure/parameter learning for neural-network-based fuzzy logic control systems
1994 · Chin-Teng Lin, C.S.G. Lee · IEEE Transactions on Fuzzy Systems · 307
Learning Bayesian Networks
2007 · R NEAPOLITAN, X JIANG · Elsevier eBooks · 275
Works count: 2,644
Citation count: 45,230
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