Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting
暂无分享,去创建一个
[1] Martin J. Wainwright,et al. Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$ -Constrained Quadratic Programming (Lasso) , 2009, IEEE Transactions on Information Theory.
[2] Pradeep Ravikumar,et al. Sparse inverse covariance matrix estimation using quadratic approximation , 2011, MLSLP.
[3] Marc Teboulle,et al. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..
[4] Stephen Gould,et al. Projected Subgradient Methods for Learning Sparse Gaussians , 2008, UAI.
[5] Paul Tseng,et al. A coordinate gradient descent method for nonsmooth separable minimization , 2008, Math. Program..
[6] Ahmad M. Al-Kandari,et al. 3 – Load Modeling for Short-Term Forecasting , 2010 .
[7] Shiqian Ma,et al. Sparse Inverse Covariance Selection via Alternating Linearization Methods , 2010, NIPS.
[8] Kyung-Ah Sohn,et al. Joint Estimation of Structured Sparsity and Output Structure in Multiple-Output Regression via Inverse-Covariance Regularization , 2012, AISTATS.
[9] Bin Yu,et al. High-dimensional covariance estimation by minimizing ℓ1-penalized log-determinant divergence , 2008, 0811.3628.
[10] Jorge Nocedal,et al. Newton-Like Methods for Sparse Inverse Covariance Estimation , 2012, NIPS.
[11] Michael I. Jordan,et al. On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes , 2001, NIPS.
[12] P. Bartlett,et al. ℓ1-regularized linear regression: persistence and oracle inequalities , 2012 .
[13] Alexandre d'Aspremont,et al. Model Selection Through Sparse Max Likelihood Estimation Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data , 2022 .
[14] Zhaosong Lu,et al. Smooth Optimization Approach for Sparse Covariance Selection , 2008, SIAM J. Optim..
[15] Pierre Pinson,et al. Global Energy Forecasting Competition 2012 , 2014 .
[16] S. Sra,et al. Matrix Differential Calculus , 2005 .
[17] Andrew McCallum,et al. An Introduction to Conditional Random Fields , 2010, Found. Trends Mach. Learn..
[18] Xiao-Tong Yuan,et al. Partial Gaussian Graphical Model Estimation , 2012, IEEE Transactions on Information Theory.
[19] R. Tibshirani,et al. Sparse inverse covariance estimation with the graphical lasso. , 2008, Biostatistics.