Fast Multinomial Logistic Regression with Group Sparsity
References
- (2015) Foundations of Linear and Generalized Linear Models (John Wiley & Sons, Hoboken, NJ).Google Scholar
- (1994) The multinomial-Poisson transformation. J. Roy. Statist. Soc. Ser. D 43(4):495–504.Google Scholar
- (2009) Simultaneous analysis of Lasso and Dantzig selector. Ann. Stat. 37(4):1705–1732.Crossref, Google Scholar
- (2006) Pattern Recognition and Machine Learning (Springer, New York).Google Scholar
- (2023) Deep Learning: Foundations and Concepts (Springer, Cham, Switzerland).Google Scholar
- (1992) Multinomial logistic regression algorithm. Ann. Inst. Statist. Math. 44(1):197–200.Crossref, Google Scholar
- (2004) Convex Optimization (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
- (2011) Statistics for High-Dimensional Data: Methods, Theory and Applications (Springer, Berlin, Heidelberg).Crossref, Google Scholar
- (2019) Error bounds for sparse classifiers in high-dimensions. Proc. 22nd Internat. Conf. Artificial Intelligence Statist. (PMLR, New York), 48–56.Google Scholar
- (2021) Improved error rates for sparse (group) learning with Lipschitz loss functions. Preprint, submitted September 22, https://arxiv.org/abs/1910.08880.Google Scholar
- (2023) Communication-efficient accurate statistical estimation. J. Amer. Statist. Assoc. 118(542):1000–1010.Crossref, Google Scholar
- (2010) Regularization paths for generalized linear models via coordinate descent. J. Statist. Software 33(1):1–22.Crossref, Google Scholar
- (2007) Pathwise coordinate optimization. Ann. Appl. Statist. 1(2):302–332.Crossref, Google Scholar
- (2023a) Simplex-based proximal multicategory support vector machine. IEEE Trans. Inform. Theory 69(4):2427–2451.Crossref, Google Scholar
- (2018) Adaptively weighted large-margin angle-based classifiers. J. Multivariate Anal. 166:282–299.Crossref, Google Scholar
- (2023b) Simplex-based multinomial logistic regression with diverging numbers of categories and covariates. Statist. Sinica 33(4):2463–2493.Google Scholar
- (2019) Robust outcome weighted learning for optimal individualized treatment rules. J. Biopharmaceutical Statist. 29(4):606–624.Crossref, Google Scholar
- (2026) Fast multinomial logistic regression with group sparsity. https://doi.org/10.1287/ijoc.2024.0796.cd, https://github.com/INFORMSJoC/2024.0796.Google Scholar
- (2012) Safe feature elimination for the LASSO and sparse supervised learning problems. Pacific J. Optim. 8(4):667–698.Google Scholar
- (2009) The Elements of Statistical Learning: Data Mining, Inference and Prediction (Springer, New York).Crossref, Google Scholar
- (2015) Statistical Learning with Sparsity: The Lasso and Generalizations (Chapman and Hall/CRC, Boca Raton, FL).Crossref, Google Scholar
- (2013) Applied Logistic Regression (John Wiley & Sons, Hoboken, NJ).Crossref, Google Scholar
- (2010) The benefit of group sparsity. Ann. Statist. 38(4):1978–2004.Crossref, Google Scholar
- (2004) A tutorial on MM algorithms. Amer. Statist. 58(1):30–37.Crossref, Google Scholar
- (2021) An Introduction to Statistical Learning: With Applications in R (Springer, New York).Crossref, Google Scholar
- (2019) Communication-efficient distributed statistical inference. J. Amer. Statist. Assoc. 114(526):668–681.Crossref, Google Scholar
- (2005) Sparse multinomial logistic regression: Fast algorithms and generalization bounds. IEEE Trans. Pattern Anal. Machine Intelligence 27(6):957–968.Crossref, Google Scholar
- (2021) A review of Bayesian group selection approaches for linear regression models. Wiley Interdisciplinary Rev. Comput. Statist. 13(4):e1513.Crossref, Google Scholar
- (2020) Managing churn to maximize profits. Marketing Sci. 39(5):956–973.Link, Google Scholar
- (2022) Applying logistic LASSO regression for the diagnosis of atypical Crohn’s disease. Sci. Rep. 12(1):11340.Crossref, Google Scholar
- (2023) Variable screening for sparse online regression. J. Comput. Graphical Statist. 32(1):275–293.Crossref, Google Scholar
- (2024) Modern approaches for evaluating treatment effect heterogeneity from clinical trials and observational data. Statist. Med. 43(22):4388–4436.Crossref, Google Scholar
- (2011) Oracle inequalities and optimal inference under group sparsity. Ann. Statist. 39(4):2164–2204.Crossref, Google Scholar
- (2025) Balancing resilience and efficiency: A literature review on overcoming supply chain disruptions. Production Oper. Management 34(6):1495–1511.Crossref, Google Scholar
- (2008) The group lasso for logistic regression. J. Roy. Statist. Soc. Ser. B 70(1):53–71.Crossref, Google Scholar
- (2022) Probabilistic Machine Learning: An Introduction (MIT Press, Cambridge, MA).Google Scholar
- (2015) GAP safe screening rules for sparse multi-task and multi-class models. Adv. Neural Inform. Processing Systems 28:811–819.Google Scholar
- (2017) Gap safe screening rules for sparsity enforcing penalties. J. Machine Learn. Res. 18(1):4671–4703.Google Scholar
- (2012) A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers. Statist. Sci. 27(4):538–557.Crossref, Google Scholar
- (2022) Multiclass-penalized logistic regression. Comput. Statist. Data Anal. 169:107414.Crossref, Google Scholar
- (2024) An integrated predictive maintenance and operations scheduling framework for power systems under failure uncertainty. INFORMS J. Comput. 36(5):1335–1358.Link, Google Scholar
- R Core Team (2023) R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna).Google Scholar
- (2019) The impact of regularization on high-dimensional logistic regression. Adv. Neural Inform. Processing Systems 32:12005–12015.Google Scholar
- (2021) Fecal bacteria as biomarkers for predicting food intake in healthy adults. J. Nutrition 151(2):423–433.Crossref, Google Scholar
- (2013) A blockwise descent algorithm for group-penalized multiresponse and multinomial regression. Preprint, submitted November 26, https://arxiv.org/abs/1311.6529.Google Scholar
- (2025) Optimal abort policy for mission-critical systems under imperfect condition monitoring. Oper. Res. 73(5):2396–2416.Link, Google Scholar
- (2024) Bayesian network models for PTSD screening in veterans. INFORMS J. Comput. 36(2):495–509.Link, Google Scholar
- (1996) Regression shrinkage and selection via the lasso. J. Roy. Statist. Soc. Ser. B 58(1):267–288.Crossref, Google Scholar
- (2012) Strong rules for discarding predictors in lasso-type problems. J. Roy. Statist. Soc. Ser. B 74(2):245–266.Crossref, Google Scholar
- (2011) Regression for Categorical Data (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
- (2014) Sparse group lasso and high dimensional multinomial classification. Comput. Statist. Data Anal. 71:771–786.Crossref, Google Scholar
- (2014) A safe screening rule for sparse logistic regression. Adv. Neural Inform. Processing Systems 27:1053–1061.Google Scholar
- (2023) Simultaneous dimension reduction and variable selection for multinomial logistic regression. INFORMS J. Comput. 35(5):1044–1060.Link, Google Scholar
- (2015) A fast unified algorithm for solving group-lasso penalize learning problems. Statist. Comput. 25(6):1129–1141.Crossref, Google Scholar
- (2020) The effect of shortening lock-in periods in telecommunication services. MIS Quart. 44(3):1391–1409.Crossref, Google Scholar
- (2006) Model selection and estimation in regression with grouped variables. J. Roy. Statist. Soc. Ser. B 68(1):49–67.Crossref, Google Scholar
- (2023) Feature screening strategy for non-convex sparse logistic regression with log sum penalty. Inform. Sci. 624:732–747.Crossref, Google Scholar
- (2021) Concentration inequalities for statistical inference. Commun. Math. Res. 37(1):1–85.Crossref, Google Scholar
- (2014) Multicategory angle-based large-margin classification. Biometrika 101(3):625–640.Crossref, Google Scholar
- (2016) Reinforced angle-based multicategory support vector machines. J. Comput. Graphical Statist. 25(3):806–825.Crossref, Google Scholar
- (2018) Robust multicategory support vector machines using difference convex algorithm. Math. Programming 169(1):277–305.Crossref, Google Scholar
- (2004) Classification of gene microarrays by penalized logistic regression. Biostatistics 5(3):427–443.Crossref, Google Scholar

