convergence rate

The Fast Convergence of Incremental PCA NeurIPS 2013 The Rate of Convergence of AdaBoost JMLR 2013 A Stochastic Gradient Method with an Exponential Convergence _Rate for Finite Training Sets NeurIPS 2012 Convergence Rate Analysis of MAP Coordinate Minimization Algorithms NeurIPS 2012 Ensemble weighted kernel estimators for multivariate entropy estimation NeurIPS 2012 Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods NeurIPS 2012 Generalization Bounds for Domain Adaptation NeurIPS 2012 Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation NeurIPS 2012 L1 Covering Numbers for Uniformly Bounded Convex Functions COLT 2012 Learning Probability Measures with respect to Optimal Transport Metrics NeurIPS 2012 Mixability in Statistical Learning NeurIPS 2012 On the Convergence Rate of -Norm Multiple Kernel Learning JMLR 2012 On the Sample Complexity of Robust PCA NeurIPS 2012 Open Problem: Is Averaging Needed for Strongly Convex Stochastic Gradient Descent? COLT 2012 Optimal Regularized Dual Averaging Methods for Stochastic Optimization NeurIPS 2012 PAC-Bayesian Bound for Gaussian Process Regression and Multiple Kernel Additive Model COLT 2012 Privacy Aware Learning NeurIPS 2012 Stochastic Gradient Descent with Only One Projection NeurIPS 2012 Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions NeurIPS 2012 Toward a Noncommutative Arithmetic-geometric Mean Inequality: Conjectures, Case-studies, and Consequences COLT 2012 Convergence Rates of Efficient Global Optimization Algorithms JMLR 2011 Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization NeurIPS 2011 Differentially Private M-Estimators NeurIPS 2011 High-dimensional Covariance Estimation Based On Gaussian Graphical Models JMLR 2011 Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent NeurIPS 2011