Distributed training of Large-scale Logistic models
暂无分享,去创建一个
[1] Jorge Nocedal,et al. On the limited memory BFGS method for large scale optimization , 1989, Math. Program..
[2] R. Rust,et al. Customer satisfaction, customer retention, and market share , 1993 .
[3] Léon Bottou,et al. Large-Scale Machine Learning with Stochastic Gradient Descent , 2010, COMPSTAT.
[4] T. Minka. A comparison of numerical optimizers for logistic regression , 2004 .
[5] B. Kirkwood. Essentials of medical statistics. , 1988 .
[6] Hal Daumé. Notes on CG and LM-BFGS Optimization of Logistic Regression , 2008 .
[7] Tong Zhang,et al. Solving large scale linear prediction problems using stochastic gradient descent algorithms , 2004, ICML.
[8] J. Darroch,et al. Generalized Iterative Scaling for Log-Linear Models , 1972 .
[9] Stephen P. Boyd,et al. Tractable approximate robust geometric programming , 2007, Optimization and Engineering.
[10] Mohammad Emtiyaz Khan,et al. Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models , 2011, ICML.
[11] David F. Shanno,et al. An example of numerical nonconvergence of a variable-metric method , 1985 .
[12] Stephen P. Boyd,et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..
[13] John D. Lafferty,et al. Dynamic topic models , 2006, ICML.
[14] Guillaume Bouchard. Efficient Bounds for the Softmax Function and Applications to Approximate Inference in Hybrid models , 2008 .
[15] Chih-Jen Lin,et al. Trust Region Newton Method for Logistic Regression , 2008, J. Mach. Learn. Res..
[16] P. Holland,et al. Robust regression using iteratively reweighted least-squares , 1977 .
[17] Fernando Pereira,et al. Shallow Parsing with Conditional Random Fields , 2003, NAACL.
[18] L. Eon Bottou. Online Learning and Stochastic Approximations , 1998 .
[19] Simon Günter,et al. A Stochastic Quasi-Newton Method for Online Convex Optimization , 2007, AISTATS.
[20] Chih-Jen Lin,et al. Dual coordinate descent methods for logistic regression and maximum entropy models , 2011, Machine Learning.