Oliver Hinder

According to our database, Oliver Hinder authored at least 22 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Worst-case analysis of restarted primal-dual hybrid gradient on totally unimodular linear programs.

Oliver Hinder

Oper. Res. Lett., 2024

Accelerated Parameter-Free Stochastic Optimization.

Itai Kreisler, Maor Ivgi, Oliver Hinder, Yair Carmon

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

The Price of Adaptivity in Stochastic Convex Optimization.

Yair Carmon, Oliver Hinder

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

Faster first-order primal-dual methods for linear programming using restarts and sharpness.

David L. Applegate, Oliver Hinder, Haihao Lu, Miles Lubin

Math. Program., 2023

Datasets and Benchmarks for Nanophotonic Structure and Parametric Design Simulations.

Jungtaek Kim, Mingxuan Li, Oliver Hinder, Paul W. Leu

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

DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule.

Maor Ivgi, Oliver Hinder, Yair Carmon

Proceedings of the International Conference on Machine Learning, 2023

2022

Optimal Diagonal Preconditioning: Theory and Practice.

Zhaonan Qu, Wenzhi Gao, Oliver Hinder, Yinyu Ye, Zhengyuan Zhou

CoRR, 2022

A consistently adaptive trust-region method.

Fadi Hamad, Oliver Hinder

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

Making SGD Parameter-Free.

Yair Carmon, Oliver Hinder

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

2021

On the behavior of Lagrange multipliers in convex and nonconvex infeasible interior point methods.

Gabriel Haeser, Oliver Hinder, Yinyu Ye

Math. Program., 2021

Lower bounds for finding stationary points II: first-order methods.

Yair Carmon, John C. Duchi, Oliver Hinder, Aaron Sidford

Math. Program., 2021

Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient.

David L. Applegate, Mateo Díaz, Oliver Hinder, Haihao Lu, Miles Lubin, Brendan O'Donoghue, Warren Schudy

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

2020

Lower bounds for finding stationary points I.

Yair Carmon, John C. Duchi, Oliver Hinder, Aaron Sidford

Math. Program., 2020

Conic Descent and its Application to Memory-efficient Optimization over Positive Semidefinite Matrices.

John C. Duchi, Oliver Hinder, Andrew Naber, Yinyu Ye

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

An efficient nonconvex reformulation of stagewise convex optimization problems.

Rudy Bunel, Oliver Hinder, Srinadh Bhojanapalli, Krishnamurthy Dvijotham

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

Near-Optimal Methods for Minimizing Star-Convex Functions and Beyond.

Oliver Hinder, Aaron Sidford, Nimit Sharad Sohoni

Proceedings of the Conference on Learning Theory, 2020

2018

Accelerated Methods for NonConvex Optimization.

Yair Carmon, John C. Duchi, Oliver Hinder, Aaron Sidford

SIAM J. Optim., 2018

A polynomial time log barrier method for problems with nonconvex constraints.

Oliver Hinder, Yinyu Ye

CoRR, 2018

Cutting plane methods can be extended into nonconvex optimization.

Oliver Hinder

Proceedings of the Conference On Learning Theory, 2018

2017

A novel integer programing formulation for scheduling with family setup times on a single machine to minimize maximum lateness.

Oliver Hinder, Andrew J. Mason

Eur. J. Oper. Res., 2017

"Convex Until Proven Guilty": Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions.

Yair Carmon, John C. Duchi, Oliver Hinder, Aaron Sidford

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Accelerated Methods for Non-Convex Optimization.

Yair Carmon, John C. Duchi, Oliver Hinder, Aaron Sidford

CoRR, 2016