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Dmitriy Drusvyatskiy
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2020 – today
- 2025
- [j38]Damek Davis, Dmitriy Drusvyatskiy
, Zhan Shi:
Stochastic Optimization Over Proximally Smooth Sets. SIAM J. Optim. 35(1): 157-179 (2025) - 2024
- [j37]Joshua Cutler, Mateo Díaz, Dmitriy Drusvyatskiy:
Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality. J. Mach. Learn. Res. 25: 90:1-90:49 (2024) - [j36]Damek Davis, Dmitriy Drusvyatskiy
, Vasileios Charisopoulos:
Stochastic algorithms with geometric step decay converge linearly on sharp functions. Math. Program. 207(1): 145-190 (2024) - [i23]Adityanarayanan Radhakrishnan, Mikhail Belkin, Dmitriy Drusvyatskiy:
Linear Recursive Feature Machines provably recover low-rank matrices. CoRR abs/2401.04553 (2024) - [i22]Damek Davis, Dmitriy Drusvyatskiy, Liwei Jiang:
Gradient descent with adaptive stepsize converges (nearly) linearly under fourth-order growth. CoRR abs/2409.19791 (2024) - 2023
- [j35]Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui:
Stochastic Optimization under Distributional Drift. J. Mach. Learn. Res. 24: 147:1-147:56 (2023) - [j34]Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff:
Multiplayer Performative Prediction: Learning in Decision-Dependent Games. J. Mach. Learn. Res. 24: 202:1-202:56 (2023) - [j33]Dmitriy Drusvyatskiy
, Lin Xiao
:
Stochastic Optimization with Decision-Dependent Distributions. Math. Oper. Res. 48(2): 954-998 (2023) - [c9]Chaoyue Liu, Dmitriy Drusvyatskiy, Misha Belkin, Damek Davis, Yi-An Ma:
Aiming towards the minimizers: fast convergence of SGD for overparametrized problems. NeurIPS 2023 - [i21]Chaoyue Liu, Dmitriy Drusvyatskiy, Mikhail Belkin, Damek Davis, Yi-An Ma:
Aiming towards the minimizers: fast convergence of SGD for overparametrized problems. CoRR abs/2306.02601 (2023) - 2022
- [j32]Damek Davis, Dmitriy Drusvyatskiy:
Proximal Methods Avoid Active Strict Saddles of Weakly Convex Functions. Found. Comput. Math. 22(2): 561-606 (2022) - [j31]Damek Davis
, Dmitriy Drusvyatskiy:
Graphical Convergence of Subgradients in Nonconvex Optimization and Learning. Math. Oper. Res. 47(1): 209-231 (2022) - [j30]Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy
:
Escaping Strict Saddle Points of the Moreau Envelope in Nonsmooth Optimization. SIAM J. Optim. 32(3): 1958-1983 (2022) - [c8]Mitas Ray, Lillian J. Ratliff, Dmitriy Drusvyatskiy, Maryam Fazel:
Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments. AAAI 2022: 8081-8088 - [c7]Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff:
Learning in Stochastic Monotone Games with Decision-Dependent Data. AISTATS 2022: 5891-5912 - [c6]Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff:
Improved Rates for Derivative Free Gradient Play in Strongly Monotone Games∗. CDC 2022: 3403-3408 - [c5]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 - [i20]Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff:
Multiplayer Performative Prediction: Learning in Decision-Dependent Games. CoRR abs/2201.03398 (2022) - [i19]Lijun Ding, Dmitriy Drusvyatskiy, Maryam Fazel:
Flat minima generalize for low-rank matrix recovery. CoRR abs/2203.03756 (2022) - [i18]Mitas Ray, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff:
Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments. CoRR abs/2204.08281 (2022) - [i17]Joshua Cutler, Mateo Díaz, Dmitriy Drusvyatskiy:
Stochastic approximation with decision-dependent distributions: asymptotic normality and optimality. CoRR abs/2207.04173 (2022) - 2021
- [j29]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): 1505-1593 (2021) - [j28]Damek Davis, Dmitriy Drusvyatskiy, Lin Xiao, Junyu Zhang:
From Low Probability to High Confidence in Stochastic Convex Optimization. J. Mach. Learn. Res. 22: 49:1-49:38 (2021) - [j27]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): 357-383 (2021) - [c4]Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui:
Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees. NeurIPS 2021: 11859-11869 - [i16]Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy:
Escaping strict saddle points of the Moreau envelope in nonsmooth optimization. CoRR abs/2106.09815 (2021) - [i15]Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui:
Stochastic optimization under time drift: iterate averaging, step decay, and high probability guarantees. CoRR abs/2108.07356 (2021) - [i14]Damek Davis, Dmitriy Drusvyatskiy, Liwei Jiang:
Subgradient methods near active manifolds: saddle point avoidance, local convergence, and asymptotic normality. CoRR abs/2108.11832 (2021) - [i13]Dmitriy Drusvyatskiy, Lillian J. Ratliff:
Improved rates for derivative free play in convex games. CoRR abs/2111.09456 (2021) - 2020
- [j26]Damek Davis, Dmitriy Drusvyatskiy, Sham M. Kakade, Jason D. Lee:
Stochastic Subgradient Method Converges on Tame Functions. Found. Comput. Math. 20(1): 119-154 (2020) - [j25]Aris Daniilidis
, Dmitriy Drusvyatskiy
:
Pathological Subgradient Dynamics. SIAM J. Optim. 30(2): 1327-1338 (2020) - [c3]Damek Davis, Dmitriy Drusvyatskiy:
High probability guarantees for stochastic convex optimization. COLT 2020: 1411-1427
2010 – 2019
- 2019
- [j24]Aleksandr Y. Aravkin
, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy:
Level-set methods for convex optimization. Math. Program. 174(1-2): 359-390 (2019) - [j23]Dmitriy Drusvyatskiy
, Courtney Paquette:
Efficiency of minimizing compositions of convex functions and smooth maps. Math. Program. 178(1-2): 503-558 (2019) - [j22]Damek Davis, Dmitriy Drusvyatskiy
:
Stochastic Model-Based Minimization of Weakly Convex Functions. SIAM J. Optim. 29(1): 207-239 (2019) - [c2]Vincent Roulet, Dmitriy Drusvyatskiy, Siddhartha S. Srinivasa, Zaïd Harchaoui:
Iterative Linearized Control: Stable Algorithms and Complexity Guarantees. ICML 2019: 5518-5527 - [i12]Vasileios Charisopoulos, Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy:
Composite optimization for robust blind deconvolution. CoRR abs/1901.01624 (2019) - [i11]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 abs/1904.10020 (2019) - [i10]Damek Davis, Dmitriy Drusvyatskiy, Vasileios Charisopoulos:
Stochastic algorithms with geometric step decay converge linearly on sharp functions. CoRR abs/1907.09547 (2019) - [i9]Damek Davis, Dmitriy Drusvyatskiy:
Robust stochastic optimization with the proximal point method. CoRR abs/1907.13307 (2019) - [i8]Damek Davis, Dmitriy Drusvyatskiy:
Active strict saddles in nonsmooth optimization. CoRR abs/1912.07146 (2019) - 2018
- [j21]Damek Davis, Dmitriy Drusvyatskiy
, Kellie J. MacPhee
, Courtney Paquette:
Subgradient Methods for Sharp Weakly Convex Functions. J. Optim. Theory Appl. 179(3): 962-982 (2018) - [j20]Dmitriy Drusvyatskiy
, Adrian S. Lewis:
Error Bounds, Quadratic Growth, and Linear Convergence of Proximal Methods. Math. Oper. Res. 43(3): 919-948 (2018) - [j19]Dmitriy Drusvyatskiy, Maryam Fazel, Scott Roy:
An Optimal First Order Method Based on Optimal Quadratic Averaging. SIAM J. Optim. 28(1): 251-271 (2018) - [j18]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): 2406-2434 (2018) - [j17]Aleksandr Y. Aravkin
, Dmitriy Drusvyatskiy
, Tristan van Leeuwen
:
Efficient Quadratic Penalization Through the Partial Minimization Technique. IEEE Trans. Autom. Control. 63(7): 2131-2138 (2018) - [c1]Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy, Julien Mairal, Zaïd Harchaoui:
Catalyst for Gradient-based Nonconvex Optimization. AISTATS 2018: 613-622 - [i7]Damek Davis, Dmitriy Drusvyatskiy:
Stochastic subgradient method converges at the rate O(k-1/4) on weakly convex functions. CoRR abs/1802.02988 (2018) - [i6]Damek Davis, Dmitriy Drusvyatskiy:
Stochastic model-based minimization of weakly convex functions. CoRR abs/1803.06523 (2018) - [i5]Damek Davis, Dmitriy Drusvyatskiy, Sham M. Kakade, Jason D. Lee:
Stochastic subgradient method converges on tame functions. CoRR abs/1804.07795 (2018) - [i4]Damek Davis, Dmitriy Drusvyatskiy, Kellie J. MacPhee:
Stochastic model-based minimization under high-order growth. CoRR abs/1807.00255 (2018) - [i3]Damek Davis, Dmitriy Drusvyatskiy:
Uniform Graphical Convergence of Subgradients in Nonconvex Optimization and Learning. CoRR abs/1810.07590 (2018) - 2017
- [j16]Dmitriy Drusvyatskiy, Henry Wolkowicz:
The Many Faces of Degeneracy in Conic Optimization. Found. Trends Optim. 3(2): 77-170 (2017) - [j15]Dmitriy Drusvyatskiy, Guoyin Li
, Henry Wolkowicz:
A note on alternating projections for ill-posed semidefinite feasibility problems. Math. Program. 162(1-2): 537-548 (2017) - [j14]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): 2301-2331 (2017) - 2016
- [j13]Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis
:
Generic Minimizing Behavior in Semialgebraic Optimization. SIAM J. Optim. 26(1): 513-534 (2016) - [i2]Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy:
Level-set methods for convex optimization. CoRR abs/1602.01506 (2016) - 2015
- [j12]Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis:
Transversality and Alternating Projections for Nonconvex Sets. Found. Comput. Math. 15(6): 1637-1651 (2015) - [j11]Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis:
Clarke Subgradients for Directionally Lipschitzian Stratifiable Functions. Math. Oper. Res. 40(2): 328-349 (2015) - [j10]Dmitriy Drusvyatskiy, Stephen A. Vavasis, Henry Wolkowicz:
Extreme point inequalities and geometry of the rank sparsity ball. Math. Program. 152(1-2): 521-544 (2015) - [j9]Dmitriy Drusvyatskiy, Alexander D. Ioffe:
Quadratic growth and critical point stability of semi-algebraic functions. Math. Program. 153(2): 635-653 (2015) - [j8]Dmitriy Drusvyatskiy, Chi-Kwong Li, Diane Christine Pelejo
, Yuen-Lam Voronin, Henry Wolkowicz:
Projection methods for quantum channel construction. Quantum Inf. Process. 14(8): 3075-3096 (2015) - [j7]Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis:
Curves of Descent. SIAM J. Control. Optim. 53(1): 114-138 (2015) - [j6]Dmitriy Drusvyatskiy, Gábor Pataki, Henry Wolkowicz:
Coordinate Shadows of Semidefinite and Euclidean Distance Matrices. SIAM J. Optim. 25(2): 1160-1178 (2015) - [j5]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): 1360-1380 (2015) - 2014
- [j4]Dmitriy Drusvyatskiy, Adrian S. Lewis:
Optimality, identifiability, and sensitivity. Math. Program. 147(1-2): 467-498 (2014) - [j3]Aris Daniilidis
, Dmitriy Drusvyatskiy, Adrian S. Lewis:
Orthogonal Invariance and Identifiability. SIAM J. Matrix Anal. Appl. 35(2): 580-598 (2014) - 2013
- [j2]Dmitriy Drusvyatskiy, Adrian S. Lewis:
Semi-algebraic functions have small subdifferentials. Math. Program. 140(1): 5-29 (2013) - [j1]Dmitriy Drusvyatskiy, Adrian S. Lewis:
Tilt Stability, Uniform Quadratic Growth, and Strong Metric Regularity of the Subdifferential. SIAM J. Optim. 23(1): 256-267 (2013) - 2011
- [i1]Boris Aronov, Dmitriy Drusvyatskiy:
Complexity of a Single Face in an Arrangement of s-Intersecting Curves. CoRR abs/1108.4336 (2011)
Coauthor Index

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last updated on 2025-02-15 00:16 CET by the dblp team
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