Dmitriy Drusvyatskiy

Vasileios Charisopoulos

Math. Program., September, 2024

Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality.

[BibT_eX]

[DOI]

Mateo Díaz

J. Mach. Learn. Res., 2024

Gradient descent with adaptive stepsize converges (nearly) linearly under fourth-order growth.

[BibT_eX]

[DOI]

Adityanarayanan Radhakrishnan

Liwei Jiang

CoRR, 2024

Linear Recursive Feature Machines provably recover low-rank matrices.

[BibT_eX]

[DOI]

Mikhail Belkin

CoRR, 2024

2023

Stochastic Optimization with Decision-Dependent Distributions.

[BibT_eX]

[DOI]

Lin Xiao

Math. Oper. Res., May, 2023

Multiplayer Performative Prediction: Learning in Decision-Dependent Games.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2023

Stochastic Optimization under Distributional Drift.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2023

Aiming towards the minimizers: fast convergence of SGD for overparametrized problems.

[BibT_eX]

[DOI]

CoRR, 2023

Aiming towards the minimizers: fast convergence of SGD for overparametrized problems.

[BibT_eX]

[DOI]

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

2022

Escaping Strict Saddle Points of the Moreau Envelope in Nonsmooth Optimization.

[BibT_eX]

[DOI]

Mateo Díaz

SIAM J. Optim., September, 2022

Graphical Convergence of Subgradients in Nonconvex Optimization and Learning.

[BibT_eX]

[DOI]

Math. Oper. Res., 2022

Proximal Methods Avoid Active Strict Saddles of Weakly Convex Functions.

[BibT_eX]

[DOI]

Found. Comput. Math., 2022

Flat minima generalize for low-rank matrix recovery.

[BibT_eX]

[DOI]

Lijun Ding

Maryam Fazel

CoRR, 2022

A gradient sampling method with complexity guarantees for Lipschitz functions in high and low dimensions.

[BibT_eX]

[DOI]

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

Improved Rates for Derivative Free Gradient Play in Strongly Monotone Games<sup>∗</sup>.

[BibT_eX]

[DOI]

Maryam Fazel

Lillian J. Ratliff

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Learning in Stochastic Monotone Games with Decision-Dependent Data.

[BibT_eX]

[DOI]

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

Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Nonsmooth optimization using Taylor-like models: error bounds, convergence, and termination criteria.

[BibT_eX]

[DOI]

Math. Program., 2021

From Low Probability to High Confidence in Stochastic Convex Optimization.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2021

Low-Rank Matrix Recovery with Composite Optimization: Good Conditioning and Rapid Convergence.

[BibT_eX]

[DOI]

Vasileios Charisopoulos

Found. Comput. Math., 2021

Improved rates for derivative free play in convex games.

[BibT_eX]

[DOI]

Lillian J. Ratliff

CoRR, 2021

Subgradient methods near active manifolds: saddle point avoidance, local convergence, and asymptotic normality.

[BibT_eX]

[DOI]

Liwei Jiang

CoRR, 2021

Stochastic optimization under time drift: iterate averaging, step decay, and high probability guarantees.

[BibT_eX]

[DOI]

CoRR, 2021

Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees.

[BibT_eX]

[DOI]

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

2020

Pathological Subgradient Dynamics.

[BibT_eX]

[DOI]

Aris Daniilidis

SIAM J. Optim., 2020

Stochastic Subgradient Method Converges on Tame Functions.

[BibT_eX]

[DOI]

Found. Comput. Math., 2020

High probability guarantees for stochastic convex optimization.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2020

2019

Stochastic Model-Based Minimization of Weakly Convex Functions.

[BibT_eX]

[DOI]

SIAM J. Optim., 2019

Efficiency of minimizing compositions of convex functions and smooth maps.

[BibT_eX]

[DOI]

Courtney Paquette

Math. Program., 2019

Level-set methods for convex optimization.

[BibT_eX]

[DOI]

Aleksandr Y. Aravkin

James V. Burke

Michael P. Friedlander

Scott Roy

Math. Program., 2019

Active strict saddles in nonsmooth optimization.

[BibT_eX]

[DOI]

CoRR, 2019

Robust stochastic optimization with the proximal point method.

[BibT_eX]

[DOI]

CoRR, 2019

Composite optimization for robust blind deconvolution.

[BibT_eX]

[DOI]

Vasileios Charisopoulos

Mateo Díaz

CoRR, 2019

Iterative Linearized Control: Stable Algorithms and Complexity Guarantees.

[BibT_eX]

[DOI]

Vincent Roulet

Siddhartha S. Srinivasa

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

2018

Efficient Quadratic Penalization Through the Partial Minimization Technique.

[BibT_eX]

[DOI]

Aleksandr Y. Aravkin

Tristan van Leeuwen

IEEE Trans. Autom. Control., 2018

An Optimal First Order Method Based on Optimal Quadratic Averaging.

[BibT_eX]

[DOI]

Maryam Fazel

Scott Roy

SIAM J. Optim., 2018

Foundations of Gauge and Perspective Duality.

[BibT_eX]

[DOI]

Aleksandr Y. Aravkin

James V. Burke

Michael P. Friedlander

Kellie J. MacPhee

SIAM J. Optim., 2018

Error Bounds, Quadratic Growth, and Linear Convergence of Proximal Methods.

[BibT_eX]

[DOI]

Math. Oper. Res., 2018

Subgradient Methods for Sharp Weakly Convex Functions.

[BibT_eX]

[DOI]

J. Optim. Theory Appl., 2018

Uniform Graphical Convergence of Subgradients in Nonconvex Optimization and Learning.

[BibT_eX]

[DOI]

CoRR, 2018

Stochastic model-based minimization under high-order growth.

[BibT_eX]

[DOI]

Kellie J. MacPhee

CoRR, 2018

Stochastic subgradient method converges at the rate O(k<sup>-1/4</sup>) on weakly convex functions.

[BibT_eX]

[DOI]

CoRR, 2018

Catalyst for Gradient-based Nonconvex Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Noisy Euclidean Distance Realization: Robust Facial Reduction and the Pareto Frontier.

[BibT_eX]

[DOI]

SIAM J. Optim., 2017

A note on alternating projections for ill-posed semidefinite feasibility problems.

[BibT_eX]

[DOI]

Guoyin Li

Math. Program., 2017

The Many Faces of Degeneracy in Conic Optimization.

[BibT_eX]

[DOI]

Found. Trends Optim., 2017

2016

Generic Minimizing Behavior in Semialgebraic Optimization.

[BibT_eX]

[DOI]

SIAM J. Optim., 2016

2015

Counting Real Critical Points of the Distance to Orthogonally Invariant Matrix Sets.

[BibT_eX]

[DOI]

Hon-leung Lee

Rekha R. Thomas

SIAM J. Matrix Anal. Appl., 2015

Coordinate Shadows of Semidefinite and Euclidean Distance Matrices.

[BibT_eX]

[DOI]

Gábor Pataki

SIAM J. Optim., 2015

Curves of Descent.

[BibT_eX]

[DOI]

SIAM J. Control. Optim., 2015

Projection methods for quantum channel construction.

[BibT_eX]

[DOI]

Chi-Kwong Li

Diane Christine Pelejo

Yuen-Lam Voronin

Quantum Inf. Process., 2015

Extreme point inequalities and geometry of the rank sparsity ball.

[BibT_eX]

[DOI]

Stephen A. Vavasis

Math. Program., 2015

Quadratic growth and critical point stability of semi-algebraic functions.

[BibT_eX]

[DOI]

Math. Program., 2015

Clarke Subgradients for Directionally Lipschitzian Stratifiable Functions.

[BibT_eX]

[DOI]

Math. Oper. Res., 2015

Transversality and Alternating Projections for Nonconvex Sets.

[BibT_eX]

[DOI]

Found. Comput. Math., 2015

2014

Orthogonal Invariance and Identifiability.

[BibT_eX]

[DOI]

Aris Daniilidis

SIAM J. Matrix Anal. Appl., 2014

Optimality, identifiability, and sensitivity.

[BibT_eX]

[DOI]

Math. Program., 2014

2013

Tilt Stability, Uniform Quadratic Growth, and Strong Metric Regularity of the Subdifferential.

[BibT_eX]

[DOI]

SIAM J. Optim., 2013

Semi-algebraic functions have small subdifferentials.

[BibT_eX]

[DOI]

Math. Program., 2013

2011

Complexity of a Single Face in an Arrangement of s-Intersecting Curves

[BibT_eX]

[DOI]

Boris Aronov