smooth function

Worst-case Error Bounds for Online Learning of Smooth Functions COLT 2026 Anytime Acceleration of Gradient Descent COLT 2025 Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses ICML 2024 When Representations Align: Universality in Representation Learning Dynamics ICML 2024 Accelerated Stochastic Optimization Methods under Quasar-convexity ICML 2023 On the complexity of finding stationary points of smooth functions in one dimension ALT 2023 Smooth Non-stationary Bandits ICML 2023 Towards Empirical Process Theory for Vector-Valued Functions: Metric Entropy of Smooth Function Classes ALT 2023 Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions L4DC 2021 Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss COLT 2021 Dynamic Regret of Convex and Smooth Functions NeurIPS 2020 How to Trap a Gradient Flow COLT 2020 Provably robust estimation of modulo 1 samples of a smooth function with applications to phase unwrapping JMLR 2020 Rational neural networks NeurIPS 2020 Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions NeurIPS 2019 Adaptive Regret of Convex and Smooth Functions ICML 2019 On denoising modulo 1 samples of a function AISTATS 2018 Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates NeurIPS 2018 Asynchronous Parallel Greedy Coordinate Descent NeurIPS 2016 A Lower Bound for the Optimization of Finite Sums ICML 2015 Spectral Bandits for Smooth Graph Functions ICML 2014 Mixed Optimization for Smooth Functions NeurIPS 2013 O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions ICML 2013