strongly convex function

Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization UAI 2019 Random Shuffling Beats SGD after Finite Epochs ICML 2019 Accelerating Greedy Coordinate Descent Methods ICML 2018 Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions ICML 2018 Dynamic Regret of Strongly Adaptive Methods ICML 2018 Minimizing Adaptive Regret with One Gradient per Iteration IJCAI 2018 Variants of RMSProp and Adagrad with Logarithmic Regret Bounds ICML 2017 A Superlinearly-Convergent Proximal Newton-type Method for the Optimization of Finite Sums ICML 2016 MetaGrad: Multiple Learning Rates in Online Learning NeurIPS 2016 Bandit Convex Optimization: Towards Tight Bounds NeurIPS 2014 Accelerating Stochastic Gradient Descent using Predictive Variance Reduction NeurIPS 2013 A Stochastic Gradient Method with an Exponential Convergence _Rate for Finite Training Sets NeurIPS 2012 Mind the Duality Gap: Logarithmic regret algorithms for online optimization NeurIPS 2008 On the Generalization Ability of Online Strongly Convex Programming Algorithms NeurIPS 2008 Adaptive Online Gradient Descent NeurIPS 2007