Dmitriy Drusvyatskiy

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 54

Top Topics

Convex Optimization

Top Venues

Math. Oper. Res.

Publications

Adityanarayanan Radhakrishnan, Mikhail Belkin, Dmitriy Drusvyatskiy
Linear Recursive Feature Machines provably recover low-rank matrices. CoRR (2024)
Damek Davis, Dmitriy Drusvyatskiy, Vasileios Charisopoulos
Stochastic algorithms with geometric step decay converge linearly on sharp functions. Math. Program. 207 (1) (2024)
Dmitriy Drusvyatskiy, Lin Xiao
Stochastic Optimization with Decision-Dependent Distributions. Math. Oper. Res. 48 (2) (2023)
Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
Multiplayer Performative Prediction: Learning in Decision-Dependent Games. J. Mach. Learn. Res. 24 (2023)
Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui
Stochastic Optimization under Distributional Drift. J. Mach. Learn. Res. 24 (2023)
Chaoyue Liu, Dmitriy Drusvyatskiy, Misha Belkin, Damek Davis, Yi-An Ma
Aiming towards the minimizers: fast convergence of SGD for overparametrized problems. NeurIPS (2023)
Chaoyue Liu, Dmitriy Drusvyatskiy, Mikhail Belkin, Damek Davis, Yi-An Ma
Aiming towards the minimizers: fast convergence of SGD for overparametrized problems. CoRR (2023)
Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy
Escaping Strict Saddle Points of the Moreau Envelope in Nonsmooth Optimization. SIAM J. Optim. 32 (3) (2022)
Damek Davis, Dmitriy Drusvyatskiy
Proximal Methods Avoid Active Strict Saddles of Weakly Convex Functions. Found. Comput. Math. 22 (2) (2022)
Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
Learning in Stochastic Monotone Games with Decision-Dependent Data. AISTATS (2022)
Damek Davis, Dmitriy Drusvyatskiy, Yin Tat Lee, Swati Padmanabhan, Guanghao Ye
A gradient sampling method with complexity guarantees for Lipschitz functions in high and low dimensions. NeurIPS (2022)
Joshua Cutler, Mateo Díaz, Dmitriy Drusvyatskiy
Stochastic approximation with decision-dependent distributions: asymptotic normality and optimality. CoRR (2022)
Damek Davis, Dmitriy Drusvyatskiy
Graphical Convergence of Subgradients in Nonconvex Optimization and Learning. Math. Oper. Res. 47 (1) (2022)
Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
Multiplayer Performative Prediction: Learning in Decision-Dependent Games. CoRR (2022)
Mitas Ray, Lillian J. Ratliff, Dmitriy Drusvyatskiy, Maryam Fazel
Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments. AAAI (2022)
Mitas Ray, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments. CoRR (2022)
Lijun Ding, Dmitriy Drusvyatskiy, Maryam Fazel
Flat minima generalize for low-rank matrix recovery. CoRR (2022)
Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff
. CDC (2022)
Dmitriy Drusvyatskiy, Lillian J. Ratliff
Improved rates for derivative free play in convex games. CoRR (2021)
Vasileios Charisopoulos, Yudong Chen, Damek Davis, Mateo Díaz, Lijun Ding, Dmitriy Drusvyatskiy
Low-Rank Matrix Recovery with Composite Optimization: Good Conditioning and Rapid Convergence. Found. Comput. Math. 21 (6) (2021)
Damek Davis, Dmitriy Drusvyatskiy, Lin Xiao, Junyu Zhang
From Low Probability to High Confidence in Stochastic Convex Optimization. J. Mach. Learn. Res. 22 (2021)
Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy
Escaping strict saddle points of the Moreau envelope in nonsmooth optimization. CoRR (2021)
Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui
Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees. NeurIPS (2021)
Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis
Nonsmooth optimization using Taylor-like models: error bounds, convergence, and termination criteria. Math. Program. 185 (1-2) (2021)
Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui
Stochastic optimization under time drift: iterate averaging, step decay, and high probability guarantees. CoRR (2021)
Damek Davis, Dmitriy Drusvyatskiy, Liwei Jiang
Subgradient methods near active manifolds: saddle point avoidance, local convergence, and asymptotic normality. CoRR (2021)
Damek Davis, Dmitriy Drusvyatskiy, Sham M. Kakade, Jason D. Lee
Stochastic Subgradient Method Converges on Tame Functions. Found. Comput. Math. 20 (1) (2020)
Damek Davis, Dmitriy Drusvyatskiy
High probability guarantees for stochastic convex optimization. COLT (2020)
Aris Daniilidis, Dmitriy Drusvyatskiy
Pathological Subgradient Dynamics. SIAM J. Optim. 30 (2) (2020)
Damek Davis, Dmitriy Drusvyatskiy
Active strict saddles in nonsmooth optimization. CoRR (2019)
Damek Davis, Dmitriy Drusvyatskiy, Vasileios Charisopoulos
Stochastic algorithms with geometric step decay converge linearly on sharp functions. CoRR (2019)
Damek Davis, Dmitriy Drusvyatskiy
Robust stochastic optimization with the proximal point method. CoRR (2019)
Vasileios Charisopoulos, Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy
Composite optimization for robust blind deconvolution. CoRR (2019)
Vincent Roulet, Dmitriy Drusvyatskiy, Siddhartha S. Srinivasa, Zaïd Harchaoui
Iterative Linearized Control: Stable Algorithms and Complexity Guarantees. ICML (2019)
Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy
Level-set methods for convex optimization. Math. Program. 174 (1-2) (2019)
Dmitriy Drusvyatskiy, Courtney Paquette
Efficiency of minimizing compositions of convex functions and smooth maps. Math. Program. 178 (1-2) (2019)
Damek Davis, Dmitriy Drusvyatskiy
Stochastic Model-Based Minimization of Weakly Convex Functions. SIAM J. Optim. 29 (1) (2019)
Vasileios Charisopoulos, Yudong Chen, Damek Davis, Mateo Díaz, Lijun Ding, Dmitriy Drusvyatskiy
Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence. CoRR (2019)
Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Kellie J. MacPhee
Foundations of Gauge and Perspective Duality. SIAM J. Optim. 28 (3) (2018)
Dmitriy Drusvyatskiy, Maryam Fazel, Scott Roy
An Optimal First Order Method Based on Optimal Quadratic Averaging. SIAM J. Optim. 28 (1) (2018)
Damek Davis, Dmitriy Drusvyatskiy, Sham M. Kakade, Jason D. Lee
Stochastic subgradient method converges on tame functions. CoRR (2018)
Dmitriy Drusvyatskiy, Adrian S. Lewis
Error Bounds, Quadratic Growth, and Linear Convergence of Proximal Methods. Math. Oper. Res. 43 (3) (2018)
Damek Davis, Dmitriy Drusvyatskiy
Stochastic model-based minimization of weakly convex functions. CoRR (2018)
Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy, Julien Mairal, Zaïd Harchaoui
Catalyst for Gradient-based Nonconvex Optimization. AISTATS (2018)
Damek Davis, Dmitriy Drusvyatskiy, Kellie J. MacPhee
Stochastic model-based minimization under high-order growth. CoRR (2018)
Aleksandr Y. Aravkin, Dmitriy Drusvyatskiy, Tristan van Leeuwen
Efficient Quadratic Penalization Through the Partial Minimization Technique. IEEE Trans. Autom. Control. 63 (7) (2018)
Damek Davis, Dmitriy Drusvyatskiy, Kellie J. MacPhee, Courtney Paquette
Subgradient Methods for Sharp Weakly Convex Functions. J. Optim. Theory Appl. 179 (3) (2018)
Damek Davis, Dmitriy Drusvyatskiy
) on weakly convex functions. CoRR (2018)
Damek Davis, Dmitriy Drusvyatskiy
Uniform Graphical Convergence of Subgradients in Nonconvex Optimization and Learning. CoRR (2018)
Dmitriy Drusvyatskiy, Henry Wolkowicz
The Many Faces of Degeneracy in Conic Optimization. Found. Trends Optim. 3 (2) (2017)
Dmitriy Drusvyatskiy, Guoyin Li, Henry Wolkowicz
A note on alternating projections for ill-posed semidefinite feasibility problems. Math. Program. 162 (1-2) (2017)
Dmitriy Drusvyatskiy, Nathan Krislock, Yuen-Lam Voronin, Henry Wolkowicz
Noisy Euclidean Distance Realization: Robust Facial Reduction and the Pareto Frontier. SIAM J. Optim. 27 (4) (2017)
Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy
Level-set methods for convex optimization. CoRR (2016)
Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis
Generic Minimizing Behavior in Semialgebraic Optimization. SIAM J. Optim. 26 (1) (2016)
Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis
Transversality and Alternating Projections for Nonconvex Sets. Found. Comput. Math. 15 (6) (2015)
Dmitriy Drusvyatskiy, Alexander D. Ioffe
Quadratic growth and critical point stability of semi-algebraic functions. Math. Program. 153 (2) (2015)
Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis
Curves of Descent. SIAM J. Control. Optim. 53 (1) (2015)
Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis
Clarke Subgradients for Directionally Lipschitzian Stratifiable Functions. Math. Oper. Res. 40 (2) (2015)
Dmitriy Drusvyatskiy, Chi-Kwong Li, Diane Christine Pelejo, Yuen-Lam Voronin, Henry Wolkowicz
Projection methods for quantum channel construction. Quantum Inf. Process. 14 (8) (2015)
Dmitriy Drusvyatskiy, Gábor Pataki, Henry Wolkowicz
Coordinate Shadows of Semidefinite and Euclidean Distance Matrices. SIAM J. Optim. 25 (2) (2015)
Dmitriy Drusvyatskiy, Hon-leung Lee, Rekha R. Thomas
Counting Real Critical Points of the Distance to Orthogonally Invariant Matrix Sets. SIAM J. Matrix Anal. Appl. 36 (3) (2015)
Dmitriy Drusvyatskiy, Stephen A. Vavasis, Henry Wolkowicz
Extreme point inequalities and geometry of the rank sparsity ball. Math. Program. 152 (1-2) (2015)
Dmitriy Drusvyatskiy, Adrian S. Lewis
Optimality, identifiability, and sensitivity. Math. Program. 147 (1-2) (2014)
Aris Daniilidis, Dmitriy Drusvyatskiy, Adrian S. Lewis
Orthogonal Invariance and Identifiability. SIAM J. Matrix Anal. Appl. 35 (2) (2014)
Dmitriy Drusvyatskiy, Adrian S. Lewis
Semi-algebraic functions have small subdifferentials. Math. Program. 140 (1) (2013)
Dmitriy Drusvyatskiy, Adrian S. Lewis
Tilt Stability, Uniform Quadratic Growth, and Strong Metric Regularity of the Subdifferential. SIAM J. Optim. 23 (1) (2013)
Boris Aronov, Dmitriy Drusvyatskiy
Complexity of a Single Face in an Arrangement of s-Intersecting Curves CoRR (2011)