The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Group lasso with overlap and graph lasso
Abstract
We propose a new penalty function which, when used as regularization for empirical risk minimization procedures, leads to sparse estimators. The support of the sparse vector is typically a union of potentially overlapping groups of co-variates defined a priori, or a set of covariates which tend to be connected to each other when a graph of covariates is given. We study theoretical properties of the estimator, and illustrate its behavior on simulated and breast cancer gene expression data.
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Cites
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482
Model Selection and Estimation in Regression with Grouped Variables
Yuan, M., & Lin, Y. (2006) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2005.00532.x · Cited by 7,261
Atomic Decomposition by Basis Pursuit
Chen, S. S., Donoho, D. L., & Saunders, M. A. (1998) · SIAM Journal on Scientific Computing · doi:10.1137/s1064827596304010 · Cited by 6,845
A Gene-Expression Signature as a Predictor of Survival in Breast Cancer
van de Vijver, M. J., He, Y. D., van 't Veer, L. J., Dai, H., Hart, A. A. M., Voskuil, D. W., Schreiber, G. J., Peterse, J. L., Roberts, C., Marton, M. J., et al. (2002) · New England Journal of Medicine · doi:10.1056/nejmoa021967 · Cited by 6,488
The Group Lasso for Logistic Regression
Meier, L., Van De Geer, S., & Bühlmann, P. (2008) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2007.00627.x · Cited by 1,674
Network‐based classification of breast cancer metastasis
Chuang, H., Lee, E., Liu, Y., Lee, D., & Ideker, T. (2007) · Molecular Systems Biology · doi:10.1038/msb4100180 · Cited by 1,431
Asymptotics for lasso-type estimators
Fu, W., & Knight, K. (2000) · The Annals of Statistics · doi:10.1214/aos/1015957397 · Cited by 1,276
On Model Selection Consistency of Lasso
ZhaoPeng, & Yubin, Y. (2006) · Journal of Machine Learning Research · doi:10.5555/1248547.1248637 · Cited by 996
Consistency of the group Lasso and multiple kernel learning
Bach, F. (2007) · arXiv (Cornell University) · doi:10.48550/arxiv.0707.3390 · Cited by 669
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Feature Selection: A Data Perspective
Li, J., Cheng, K., Wang, S., Morstatter, F., Trevino, R. P., Tang, J., & Liu, H. (2018) · ACM Computing Surveys · doi:10.1145/3136625 · Cited by 2,442
Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data
Karpatne, A., Atluri, G., Faghmous, J. H., Steinbach, M., Banerjee, A., Ganguly, A., Shekhar, S., Samatova, N., & Kumar, V. (2017) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2017.2720168 · Cited by 1,752
Simon, N., Friedman, J., Hastie, T., & Tibshirani, R. (2013) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.2012.681250 · Cited by 1,380
Optimization with Sparsity-Inducing Penalties
Bach, F. (2011) · now publishers, Inc. eBooks · doi:10.1561/9781601985118 · Cited by 608
Quantum machine learning: a classical perspective
Ciliberto, C., Herbster, M., Ialongo, A. D., Pontil, M., Rocchetto, A., Severini, S., & Wossnig, L. (2018) · Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rspa.2017.0551 · Cited by 518
Metadata
- Authors
- Jacob, L., Obozinski, G., & Vert, J.-P.
- Venue
- Proceedings of the 26th Annual International Conference on Machine Learning
- Publisher
- ACM
- Published
- 2009-06-14
- Pages
- 433-440
- OpenAlex
- W1970554427
- Cited by
- 833
- References
- 15
- FWCI
- 144.12
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Jacob, L., Obozinski, G., & Vert, J.-P. (2009). Group lasso with overlap and graph lasso. Proceedings of the 26th Annual International Conference on Machine Learning. https://doi.org/10.1145/1553374.1553431
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
