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Keyword

sparse regression

Description: Statistical and machine learning methods that fit regression models while selecting a limited number of relevant predictors.
OpenAlex ID: keywords/sparse-regression
Model Selection and Estimation in Regression with Grouped Variables
2005 · Ming Yuan, Yi Lin · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 7,261
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Discovering governing equations from data by sparse identification of nonlinear dynamical systems
2016 · Steven L. Brunton, Joshua L. Proctor, et al. · Proceedings of the National Academy of Sciences · 4,772
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Sparse Principal Component Analysis
2006 · Hui Zou, Trevor Hastie, et al. · Journal of Computational and Graphical Statistics · 3,151
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches
2012 · José M. Bioucas-Dias, Antonio Plaza, et al. · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2,834
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Statistical Learning with Sparsity
2015 · Trevor Hastie, Robert Tibshirani, et al. · Chapman & Hall/CRC eBooks · 2,533
Data-driven discovery of partial differential equations
2017 · Samuel H. Rudy, Steven L. Brunton, et al. · Science Advances · 1,550
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High-Dimensional Probability
2018 · Roman Vershynin · Cambridge University Press eBooks · 1,397
Asymptotics for lasso-type estimators
2000 · Wenjiang Fu, Keith Knight · The Annals of Statistics · 1,275
Sparse Unmixing of Hyperspectral Data
2011 · Marian-Daniel Iordache, José M. Bioucas-Dias, et al. · IEEE Transactions on Geoscience and Remote Sensing · 1,058
Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models
2013 · Cun-Hui Zhang, Stephanie S. Zhang · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 994
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On the “degrees of freedom” of the lasso
2007 · Hui Zou, Trevor Hastie, et al. · The Annals of Statistics · 961
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Single-Image Super-Resolution Using Sparse Regression and Natural Image Prior
2010 · Kwang In Kim, Younghee Kwon · IEEE Transactions on Pattern Analysis and Machine Intelligence · 959
High-Dimensional Probability: An Introduction with Applications in Data Science
2018 · Roman Vershynin · 937
A 17-gene stemness score for rapid determination of risk in acute leukaemia
2016 · Stanley W. K. Ng, Amanda Mitchell, et al. · Nature · 911
Data-driven discovery of coordinates and governing equations
2019 · Kathleen Champion, Bethany Lusch, et al. · Proceedings of the National Academy of Sciences · 906
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L 1-Regularization Path Algorithm for Generalized Linear Models
2007 · Mee Young Park, Trevor Hastie · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 839
The solution path of the generalized lasso
2011 · Ryan J. Tibshirani, Jonathan Taylor · The Annals of Statistics · 829
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Polygenic Modeling with Bayesian Sparse Linear Mixed Models
2013 · Xiang Zhou, Peter Carbonetto, et al. · PLoS Genetics · 800
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Fast Marginal Likelihood Maximisation for Sparse Bayesian Models
2003 · Michael E. Tipping, Anita Faul · 774
Total Variation Spatial Regularization for Sparse Hyperspectral Unmixing
2012 · Marian-Daniel Iordache, José M. Bioucas-Dias, et al. · IEEE Transactions on Geoscience and Remote Sensing · 753
Statistical Learning with Sparsity: The Lasso and Generalizations
2016 · Carl M. O'Brien · International Statistical Review · 726
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Controlling the false discovery rate via knockoffs
2015 · Rina Foygel Barber, Emmanuel J. Candès · The Annals of Statistics · 725
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Partial Correlation Estimation by Joint Sparse Regression Models
2009 · Jie Peng, Pei Wang, et al. · Journal of the American Statistical Association · 688
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A note on the group lasso and a sparse group lasso
2010 · Friedman, J., Hastie, T., et al. · arXiv (Cornell University) · 642
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Physics-informed learning of governing equations from scarce data
2021 · Zhao Chen, Yang Liu, et al. · Nature Communications · 615
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Works count: 3,435
Citation count: 84,420
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