Ashok Cutkosky

Abhradeep Guha Thakurta

Alexey Kurakin

Trans. Mach. Learn. Res., 2023

Differentially Private Image Classification from Features.

[BibT_eX]

[DOI]

Walid Krichene

Abhradeep Guha Thakurta

Alexey Kurakin

Trans. Mach. Learn. Res., 2023

When, Why and How Much? Adaptive Learning Rate Scheduling by Refinement.

[BibT_eX]

[DOI]

Aaron Defazio

Konstantin Mishchenko

CoRR, 2023

Improving Adaptive Online Learning Using Refined Discretization.

[BibT_eX]

[DOI]

Heng Yang

CoRR, 2023

Unconstrained Dynamic Regret via Sparse Coding.

[BibT_eX]

[DOI]

CoRR, 2023

Blackbox optimization of unimodal functions.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Unconstrained Dynamic Regret via Sparse Coding.

[BibT_eX]

[DOI]

Yannis Paschalidis

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Mechanic: A Learning Rate Tuner.

[BibT_eX]

[DOI]

Aaron Defazio

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Alternation makes the adversary weaker in two-player games.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Unconstrained Online Learning with Unbounded Losses.

[BibT_eX]

[DOI]

Andrew Jacobsen

Proceedings of the International Conference on Machine Learning, 2023

Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Bandit Online Linear Optimization with Hints and Queries.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Long Range Language Modeling via Gated State Spaces.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Understanding AdamW through Proximal Methods and Scale-Freeness.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2022

Optimal Parameter-free Online Learning with Switching Cost.

[BibT_eX]

[DOI]

CoRR, 2022

Large Scale Transfer Learning for Differentially Private Image Classification.

[BibT_eX]

[DOI]

CoRR, 2022

Differentially Private Online-to-batch for Smooth Losses.

[BibT_eX]

[DOI]

Qinzi Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Parameter-free Regret in High Probability with Heavy Tails.

[BibT_eX]

[DOI]

Jiujia Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Momentum Aggregation for Private Non-convex ERM.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Better SGD using Second-order Momentum.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Optimal Comparator Adaptive Online Learning with Switching Cost.

[BibT_eX]

[DOI]

Yannis Paschalidis

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

PDE-Based Optimal Strategy for Unconstrained Online Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Parameter-free Mirror Descent.

[BibT_eX]

[DOI]

Andrew Jacobsen

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Leveraging Initial Hints for Free in Stochastic Linear Bandits.

[BibT_eX]

[DOI]

Christoph Dann

Abhimanyu Das

Qiuyi (Richard) Zhang

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Implicit Parameter-free Online Learning with Truncated Linear Models.

[BibT_eX]

[DOI]

Keyi Chen

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Adversarial Tracking Control via Strongly Adaptive Online Learning with Memory.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Correcting Momentum with Second-order Information.

[BibT_eX]

[DOI]

CoRR, 2021

Strongly Adaptive OCO with Memory.

[BibT_eX]

[DOI]

CoRR, 2021

Online Selective Classification with Limited Feedback.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

High-probability Bounds for Non-Convex Stochastic Optimization with Heavy Tails.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Logarithmic Regret from Sublinear Hints.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Dynamic Balancing for Model Selection in Bandits and RL.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Robust Pure Exploration in Linear Bandits with Limited Budget.

[BibT_eX]

[DOI]

Ayya Alieva

Abhimanyu Das

Proceedings of the 38th International Conference on Machine Learning, 2021

Extreme Memorization via Scale of Initialization.

[BibT_eX]

[DOI]

Behnam Neyshabur

Proceedings of the 9th International Conference on Learning Representations, 2021

Power of Hints for Online Learning with Movement Costs.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Upper Confidence Bounds for Combining Stochastic Bandits.

[BibT_eX]

[DOI]

Abhimanyu Das

Manish Purohit

CoRR, 2020

Adaptive Online Learning with Varying Norms.

[BibT_eX]

[DOI]

CoRR, 2020

Comparator-Adaptive Convex Bandits.

[BibT_eX]

[DOI]

Dirk van der Hoeven

Haipeng Luo

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Better Full-Matrix Regret via Parameter-Free Online Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Online Linear Optimization with Many Hints.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Momentum Improves Normalized SGD.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Parameter-free, Dynamic, and Strongly-Adaptive Online Learning.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Online Learning with Imperfect Hints.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Anytime Online-to-Batch Conversions, Optimism, and Acceleration.

[BibT_eX]

[DOI]

CoRR, 2019

Artificial Constraints and Lipschitz Hints for Unconstrained Online Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration.

[BibT_eX]

[DOI]

Kwang-Sung Jun

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Momentum-Based Variance Reduction in Non-Convex SGD.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization.

[BibT_eX]

[DOI]

Zhenxun Zhuang

Proceedings of the 36th International Conference on Machine Learning, 2019

Matrix-Free Preconditioning in Online Learning.

[BibT_eX]

[DOI]

Tamás Sarlós

Proceedings of the 36th International Conference on Machine Learning, 2019

Anytime Online-to-Batch, Optimism and Acceleration.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Combining Online Learning Guarantees.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2019

Artificial Constraints and Hints for Unbounded Online Learning.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2019

2018

Algorithms and lower bounds for parameter-free online learning.

[BibT_eX]

[DOI]

PhD thesis, 2018

Distributed Stochastic Optimization via Adaptive Stochastic Gradient Descent.

[BibT_eX]

[DOI]

Róbert Busa-Fekete

CoRR, 2018

Distributed Stochastic Optimization via Adaptive SGD.

[BibT_eX]

[DOI]

Róbert Busa-Fekete

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Black-Box Reductions for Parameter-free Online Learning in Banach Spaces.

[BibT_eX]

[DOI]

Proceedings of the Conference On Learning Theory, 2018

2017

Stochastic and Adversarial Online Learning without Hyperparameters.

[BibT_eX]

[DOI]

Kwabena Boahen

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Online Learning Without Prior Information.

[BibT_eX]

[DOI]

Kwabena Boahen

Proceedings of the 30th Conference on Learning Theory, 2017

2016

Online Convex Optimization with Unconstrained Domains and Losses.

[BibT_eX]

[DOI]