conftrace_

strongly convex function

31 papers

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Co-occurring keywords

convex optimization (1321) gradient descent (1144) regret bound (1926) strongly convex (89) online learning (1777) stochastic gradient descent (1091) convergence rate (607) stochastic method (95) strong convexity (59) online gradient descent (39)

Papers

Optimal Decentralized Composite Optimization for Strongly Convex Functions JMLR 2025
Estimating the Minimizer and the Minimum Value of a Regression Function under Passive Design JMLR 2024
A Simple and Optimal Approach for Universal Online Learning with Gradient Variations NIPS 2024
Universal Online Convex Optimization with $1$ Projection per Round NIPS 2024
Gradient-free optimization of highly smooth functions: improved analysis and a new algorithm JMLR 2024
User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates AISTATS 2024
Faster Accelerated First-order Methods for Convex Optimization with Strongly Convex Function Constraints NIPS 2024
Almost Sure Convergence Rates Analysis and Saddle Avoidance of Stochastic Gradient Methods JMLR 2024
On a Class of Gibbs Sampling over Networks COLT 2023
Large deviations rates for stochastic gradient descent with strongly convex functions AISTATS 2023
Adaptive Bandit Convex Optimization with Heterogeneous Curvature COLT 2022
On Online Optimization: Dynamic Regret Analysis of Strongly Convex and Smooth Problems AAAI 2021
Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions L4DC 2021
Revisiting Projection-free Online Learning: the Strongly Convex Case AISTATS 2021
Closing the convergence gap of SGD without replacement ICML 2020
Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization NIPS 2020
Trading-Off Static and Dynamic Regret in Online Least-Squares and Beyond AAAI 2020
Robust Asynchronous Stochastic Gradient-Push: Asymptotically Optimal and Network-Independent Performance for Strongly Convex Functions JMLR 2020
Linear Convergence of Adaptive Stochastic Gradient Descent AISTATS 2020
Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous Bandits NIPS 2020
Random Shuffling Beats SGD after Finite Epochs ICML 2019
Accelerating Greedy Coordinate Descent Methods ICML 2018
Minimizing Adaptive Regret with One Gradient per Iteration IJCAI 2018
Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions ICML 2018
Dynamic Regret of Strongly Adaptive Methods ICML 2018