Accelerated Methods for Non-Convex Optimization. - Yair Carmon; John C. Duchi; Oliver Hinder; Aaron Sidford (CoRR, 2016)

"Convex Until Proven Guilty": Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions. - Yair Carmon; John C. Duchi; Oliver Hinder; Aaron Sidford (ICML, 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)

Cutting plane methods can be extended into nonconvex optimization. - Oliver Hinder (COLT, 2018)

A polynomial time log barrier method for problems with nonconvex constraints. - Oliver Hinder; Yinyu Ye 001 (CoRR, 2018)

Accelerated Methods for NonConvex Optimization. - Yair Carmon; John C. Duchi; Oliver Hinder; Aaron Sidford (SIAM J. Optim., 2018)

Near-Optimal Methods for Minimizing Star-Convex Functions and Beyond. - Oliver Hinder; Aaron Sidford; Nimit Sharad Sohoni (COLT, 2020)

An efficient nonconvex reformulation of stagewise convex optimization problems. - Rudy Bunel; Oliver Hinder; Srinadh Bhojanapalli; Krishnamurthy Dvijotham (NeurIPS, 2020)

Conic Descent and its Application to Memory-efficient Optimization over Positive Semidefinite Matrices. - John C. Duchi; Oliver Hinder; Andrew Naber; Yinyu Ye 001 (NeurIPS, 2020)

Lower bounds for finding stationary points I. - Yair Carmon; John C. Duchi; Oliver Hinder; Aaron Sidford (Math. Program., 2020)

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 (NeurIPS, 2021)

Lower bounds for finding stationary points II: first-order methods. - Yair Carmon; John C. Duchi; Oliver Hinder; Aaron Sidford (Math. Program., 2021)

On the behavior of Lagrange multipliers in convex and nonconvex infeasible interior point methods. - Gabriel Haeser; Oliver Hinder; Yinyu Ye 001 (Math. Program., 2021)

Making SGD Parameter-Free. - Yair Carmon; Oliver Hinder (COLT, 2022)

A consistently adaptive trust-region method. - Fadi Hamad; Oliver Hinder (NeurIPS, 2022)

Optimal Diagonal Preconditioning: Theory and Practice. - Zhaonan Qu; Wenzhi Gao; Oliver Hinder; Yinyu Ye 001; Zhengyuan Zhou (CoRR, 2022)

DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule. - Maor Ivgi; Oliver Hinder; Yair Carmon (ICML, 2023)

Datasets and Benchmarks for Nanophotonic Structure and Parametric Design Simulations. - Jungtaek Kim 001; Mingxuan Li; Oliver Hinder; Paul W. Leu (NeurIPS, 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)

The Price of Adaptivity in Stochastic Convex Optimization. - Yair Carmon; Oliver Hinder (COLT, 2024)

Accelerated Parameter-Free Stochastic Optimization. - Itai Kreisler; Maor Ivgi; Oliver Hinder; Yair Carmon (COLT, 2024)

Worst-Case Iteration Bounds for Log Barrier Methods on Problems with Nonconvex Constraints. - Oliver Hinder; Yinyu Ye 001 (Math. Oper. Res., 2024)

Worst-case analysis of restarted primal-dual hybrid gradient on totally unimodular linear programs. - Oliver Hinder (Oper. Res. Lett., 2024)

Optimal Diagonal Preconditioning. - Zhaonan Qu; Wenzhi Gao; Oliver Hinder; Yinyu Ye 001; Zhengyuan Zhou (Oper. Res., 2025)

The Sample Complexity of Parameter-Free Stochastic Convex Optimization. - Jared Lawrence; Ari Kalinsky; Hannah Bradfield; Yair Carmon; Oliver Hinder (CoRR, 2025)