Sparsity and Smoothness Via the Fused Lasso
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2004/12/13
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Indian UGC (journal)
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Refrences23
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Citations1,326
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Robert Tibshirani Stanford University , USA
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Michael Saunders Stanford University , USA
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Saharon Rosset IBM T. J. Watson Research Center , Yorktown Heights , USA
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Ji Zhu University of Michigan , Ann Arbor , USA
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Keith Knight University of Toronto , Canada
Abstract
Cite
Tibshirani, Robert, et al. “Sparsity and Smoothness Via the Fused Lasso”. Journal of the Royal Statistical Society Series B: Statistical Methodology, vol. 67, no. 1, 2004, pp. 91-108, https://doi.org/10.1111/j.1467-9868.2005.00490.x.
Tibshirani, R., Saunders, M., Rosset, S., Zhu, J., & Knight, K. (2004). Sparsity and Smoothness Via the Fused Lasso. Journal of the Royal Statistical Society Series B: Statistical Methodology, 67(1), 91-108. https://doi.org/10.1111/j.1467-9868.2005.00490.x
Tibshirani, Robert, Michael Saunders, Saharon Rosset, Ji Zhu, and Keith Knight. “Sparsity and Smoothness Via the Fused Lasso”. Journal of the Royal Statistical Society Series B: Statistical Methodology 67, no. 1 (2004): 91-108. https://doi.org/10.1111/j.1467-9868.2005.00490.x.
Tibshirani R, Saunders M, Rosset S, Zhu J, Knight K. Sparsity and Smoothness Via the Fused Lasso. Journal of the Royal Statistical Society Series B: Statistical Methodology. 2004;67(1):91-108.
Journal Categories
Science
Mathematics
Science
Mathematics
Probabilities
Mathematical statistics
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Use of proteomic patterns in serum to identify ovarian cancer | 2002 | |||
Diagnosis of multiple cancer types by shrunken centroids of gene expression | Proceedings of the National Academy of Sciences |
| 1,760 | 2001 |
| Atomic decomposition by basis pursuit | SIAM Review |
| 2001 | |
Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring | Science |
| 5,784 | 1999 |
| Ideal spatial adaptation by wavelet shrinkage | Biometrika |
| 3,464 | 1994 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Sparse multiway canonical correlation analysis for multimodal stroke recovery data | Biometrical Journal |
| 2024 | |
Revealing genomic heterogeneity and commonality: A penalized integrative analysis approach accounting for the adjacency structure of measurements | Genetic Epidemiology |
| 2024 | |
Detecting changes in the transmission rate of a stochastic epidemic model | Statistics in Medicine |
| 2024 | |
Network alternating direction method of multipliers for ultrahigh‐dimensional decentralised federated learning | Stat |
| 2024 | |
| Adaptive hypergraph regularized logistic regression model for bioinformatic selection and classification | Applied Intelligence |
| 2024 |
Citations Analysis
The category
Science: Mathematics 595
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Nonparametric Inference for Local Extrema with Application to Oligonucleotide Microarray Data in Yeast Genome and was published in 2005. The most recent citation comes from a 2024 study titled Knowledge-guided Learning Methods for Integrative Analysis of Multi-omics Data. This article reached its peak citation in 2019, with 135 citations. It has been cited in 437 different journals, 17% of which are open access. Among related journals, the Computational Statistics & Data Analysis cited this research the most, with 43 citations. The chart below illustrates the annual citation trends for this article.