D. Drusvyatskiy

发表

Complexity of finding near-stationary points of convex functions stochastically

Damek Davis, D. Drusvyatskiy, 2018, 1802.08556.

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

Dmitriy Drusvyatskiy, Adrian S. Lewis, A. Lewis, 2016, Math. Oper. Res..

Second-order growth, tilt stability, and metric regularity of the subdifferential

D. Drusvyatskiy, B. Mordukhovich, T. Nghia, 2013, 1304.7385.

Efficiency of minimizing compositions of convex functions and smooth maps

Dmitriy Drusvyatskiy, Courtney Paquette, D. Drusvyatskiy, 2016, Math. Program..

Subgradient Methods for Sharp Weakly Convex Functions

Dmitriy Drusvyatskiy, Damek Davis, Kellie J. MacPhee, 2018, Journal of Optimization Theory and Applications.

The nonsmooth landscape of phase retrieval

Damek Davis, D. Drusvyatskiy, Courtney Paquette, 2017, IMA Journal of Numerical Analysis.

An Optimal First Order Method Based on Optimal Quadratic Averaging

Dmitriy Drusvyatskiy, Scott Roy, Maryam Fazel, 2016, SIAM J. Optim..

Noisy sensor network localization: robust facial reduction and the Pareto Frontier

H. Wolkowicz, D. Drusvyatskiy, Nathan Krislock, 2014 .

Stochastic Subgradient Method Converges on Tame Functions

Dmitriy Drusvyatskiy, Sham M. Kakade, Jason D. Lee, 2018, Foundations of Computational Mathematics.

Catalyst Acceleration for Gradient-Based Non-Convex Optimization

Z. Harchaoui, J. Mairal, D. Drusvyatskiy, 2017, 1703.10993.

Counting real critical points of the distance to spectral matrix sets

Rekha R. Thomas, D. Drusvyatskiy, Hon-leung Lee, 2015 .

SLOPE AND GEOMETRY IN VARIATIONAL MATHEMATICS

D. Drusvyatskiy, 2013 .

Approximating functions on stratified sets

D. Drusvyatskiy, M. Larsson, D. Drusvyatskiy, 2012, 1207.5258.

High probability guarantees for stochastic convex optimization

Damek Davis, D. Drusvyatskiy, 2020, COLT 2020.

Graphical Convergence of Subgradients in Nonconvex Optimization and Learning

Damek Davis, D. Drusvyatskiy, 2018, Math. Oper. Res..

Projection methods in quantum information science

H. Wolkowicz, D. Drusvyatskiy, Chi-Kwong Li, 2014, 1407.6604.

Variable projection without smoothness

Dmitriy Drusvyatskiy, Aleksandr Y. Aravkin, Tristan van Leeuwen, 2016 .

N ov 2 01 2 Clarke subgradients for directionally Lipschitzian stratifiable functions

A. Lewis, D. Drusvyatskiy, A. Ioffe, 2012 .

Trajectories of Descent

A. Lewis, D. Drusvyatskiy, A. Ioffe, 2012 .

Sweeping by a tame process

A. Daniilidis, D. Drusvyatskiy, 2014, 1412.8581.

The dimension of semialgebraic subdifferential graphs

A. Lewis, D. Drusvyatskiy, A. Ioffe, 2011, 1102.4050.

Composite optimization for robust rank one bilinear sensing

Damek Davis, D. Drusvyatskiy, Vasileios Charisopoulos, 2020 .

From Low Probability to High Confidence in Stochastic Convex Optimization

Damek Davis, D. Drusvyatskiy, Junyu Zhang, 2019, J. Mach. Learn. Res..

Stochastic approximation with decision-dependent distributions: asymptotic normality and optimality

D. Drusvyatskiy, M. D'iaz, Joshua Cutler, 2022, ArXiv.

Alternating projections and coupling slope

A. Lewis, D. Drusvyatskiy, A. Ioffe, 2014 .

Pathological Subgradient Dynamics

Dmitriy Drusvyatskiy, Aris Daniilidis, A. Daniilidis, 2019, SIAM J. Optim..

Proximal Methods Avoid Active Strict Saddles of Weakly Convex Functions

Damek Davis, D. Drusvyatskiy, 2021, Foundations of Computational Mathematics.

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

D. Drusvyatskiy, Guoyin Li, Henry Wolkowicz, 2017, Math. Program..

Transversality and Alternating Projections for Nonconvex Sets

A. Lewis, D. Drusvyatskiy, A. Ioffe, 2015, Foundations of Computational Mathematics.

Subgradient Methods for Sharp Weakly Convex Functions

Kellie J. MacPhee, Damek Davis, D. Drusvyatskiy, 2018, Journal of Optimization Theory and Applications.

Stochastic Subgradient Method Converges on Tame Functions

Jason D. Lee, S. Kakade, Damek Davis, 2019, Foundations of Computational Mathematics.

Efficiency of minimizing compositions of convex functions and smooth maps

D. Drusvyatskiy, C. Paquette, 2018, Mathematical Programming.

Extreme point inequalities and geometry of the rank sparsity ball

S. Vavasis, D. Drusvyatskiy, Henry Wolkowicz, 2014, Mathematical Programming.

The euclidean distance degree of orthogonally invariant matrix varieties

G. Ottaviani, D. Drusvyatskiy, Hon-leung Lee, 2017, Israel Journal of Mathematics.

Active manifolds, stratifications, and convergence to local minima in nonsmooth optimization

Damek Davis, D. Drusvyatskiy, L. Jiang, 2021, 2108.11832.

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

Damek Davis, D. Drusvyatskiy, Yudong Chen, 2021, Foundations of Computational Mathematics.

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

A. Lewis, D. Drusvyatskiy, A. Ioffe, 2019, Mathematical Programming.

Stochastic Optimization with Decision-Dependent Distributions

D. Drusvyatskiy, Lin Xiao, 2020, Math. Oper. Res..

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

Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis, 2016, Mathematical Programming.

Stochastic algorithms with geometric step decay converge linearly on sharp functions pdf

Dmitriy Drusvyatskiy, Vasileios Charisopoulos, Damek Davis, 2019, Mathematical Programming.

Catalyst for Gradient-based Nonconvex Optimization

Zaïd Harchaoui, Dmitriy Drusvyatskiy, Julien Mairal, 2018, AISTATS.

The proximal point method revisited

D. Drusvyatskiy, 2017, 1712.06038.

An accelerated algorithm for minimizing convex compositions

Dmitriy Drusvyatskiy, Courtney Kempton, D. Drusvyatskiy, 2016 .

The Many Faces of Degeneracy in Conic Optimization

Dmitriy Drusvyatskiy, Henry Wolkowicz, D. Drusvyatskiy, 2017, Found. Trends Optim..

Multiplayer Performative Prediction: Learning in Decision-Dependent Games

L. Ratliff, D. Drusvyatskiy, Evan Faulkner, 2022, J. Mach. Learn. Res..

Uniform Graphical Convergence of Subgradients in Nonconvex Optimization and Learning pdf

Dmitriy Drusvyatskiy, Damek Davis, Damek Davis, 2018, Math. Oper. Res..

Iterative Linearized Control: Stable Algorithms and Complexity Guarantees

Siddhartha S. Srinivasa, Zaïd Harchaoui, Dmitriy Drusvyatskiy, 2019, ICML.

Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments

L. Ratliff, D. Drusvyatskiy, Mitas Ray, 2022, AAAI.

Stochastic model-based minimization of weakly convex functions

Dmitriy Drusvyatskiy, Damek Davis, Damek Davis, 2018, SIAM J. Optim..

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

Damek Davis, D. Drusvyatskiy, Y. Lee, 2021, NeurIPS.

Escaping strict saddle points of the Moreau envelope in nonsmooth optimization pdf

Dmitriy Drusvyatskiy, Damek Davis, Mateo D'iaz, 2021, SIAM J. Optim..

Stochastic subgradient method converges at the rate O(k-1/4) on weakly convex functions pdf

Dmitriy Drusvyatskiy, Damek Davis, Damek Davis, 2018, ArXiv.

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

Dmitriy Drusvyatskiy, Adrian S. Lewis, A. Lewis, 2012, SIAM J. Optim..

Stochastic optimization over proximally smooth sets

Dmitriy Drusvyatskiy, Damek Davis, Zhan Shi, 2020, 2002.06309.

Curves of Descent

Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis, 2012, SIAM J. Control. Optim..

Projection methods for quantum channel construction

Dmitriy Drusvyatskiy, Chi-Kwong Li, Henry Wolkowicz, 2015, Quantum Information Processing.

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

Dmitriy Drusvyatskiy, Yudong Chen, Vasileios Charisopoulos, 2019, Found. Comput. Math..

Composite optimization for robust blind deconvolution pdf

Dmitriy Drusvyatskiy, Vasileios Charisopoulos, Damek Davis, 2019, ArXiv.

Conservative and Semismooth Derivatives are Equivalent for Semialgebraic Maps

Dmitriy Drusvyatskiy, Damek Davis, Damek Davis, 2021, Set-Valued and Variational Analysis.

Generic Minimizing Behavior in Semialgebraic Optimization

Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis, 2015, SIAM J. Optim..

Counting real critical points of the distance to spectral matrix sets

Rekha R. Thomas, Dmitriy Drusvyatskiy, Hon-leung Lee, 2015, 1502.02074.

Quadratic growth and critical point stability of semi-algebraic functions

D. Drusvyatskiy, A. Ioffe, 2014, Mathematical Programming.

Transversality and Alternating Projections for Nonconvex Sets

Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis, 2014, Found. Comput. Math..

Optimality, identifiability, and sensitivity

A. Lewis, D. Drusvyatskiy, 2013, Mathematical Programming.

Quadratic growth and critical point stability of semi-algebraic functions

Dmitriy Drusvyatskiy, Alexander D. Ioffe, D. Drusvyatskiy, 2013, Math. Program..

Clarke Subgradients for Directionally Lipschitzian Stratifiable Functions

Dmitriy Drusvyatskiy, Alexander D. Ioffe, Adrian S. Lewis, 2012, Math. Oper. Res..

Optimality, identifiability, and sensitivity

Dmitriy Drusvyatskiy, Adrian S. Lewis, A. Lewis, 2012, Math. Program..

Semi-algebraic functions have small subdifferentials

Dmitriy Drusvyatskiy, Adrian S. Lewis, A. Lewis, 2010, Math. Program..

APPROXIMATING FUNCTIONS ON STRATIFIABLE SETS

D. Drusvyatskiy, D. DRUSVYATSKIY, 2012 .

Asymptotic normality and optimality in nonsmooth stochastic approximation

Damek Davis, D. Drusvyatskiy, L. Jiang, 2023, 2301.06632.

Proximal Methods Avoid Active Strict Saddles of Weakly Convex Functions

Dmitriy Drusvyatskiy, Damek Davis, Damek Davis, 2021, Found. Comput. Math..

Active strict saddles in nonsmooth optimization pdf

Dmitriy Drusvyatskiy, Damek Davis, Damek Davis, 2019, ArXiv.

Variational analysis of spectral functions simplified

D. Drusvyatskiy, D. Drusvyatskiy, C. Kempton, 2015, 1506.05170.

Orthogonal Invariance and Identifiability

Dmitriy Drusvyatskiy, Adrian S. Lewis, Aris Daniilidis, 2013, SIAM J. Matrix Anal. Appl..

Level-set methods for convex optimization

Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy, 2016, Mathematical Programming.

The euclidean distance degree of orthogonally invariant matrix varieties

Rekha R. Thomas, Dmitriy Drusvyatskiy, Giorgio Ottaviani, 2016, Israel Journal of Mathematics.

Stochastic model-based minimization under high-order growth pdf

Dmitriy Drusvyatskiy, Damek Davis, Kellie J. MacPhee, 2018, ArXiv.

Projection methods for quantum channel construction

D. Drusvyatskiy, Chi-Kwong Li, D. Pelejo, 2015, Quantum Inf. Process..

Flat minima generalize for low-rank matrix recovery

D. Drusvyatskiy, Lijun Ding, Maryam Fazel, 2022, Information and Inference: A Journal of the IMA.

A gradient sampling method with complexity guarantees for general Lipschitz functions

Dmitriy Drusvyatskiy, Damek Davis, Damek Davis, 2021 .

Stochastic Optimization under Distributional Drift

D. Drusvyatskiy, Joshua Cutler, Zaïd Harchaoui, 2021, J. Mach. Learn. Res..

From Low Probability to High Confidence in Stochastic Convex Optimization

Lin Xiao, Dmitriy Drusvyatskiy, Damek Davis, 2019, J. Mach. Learn. Res..

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

Dmitriy Drusvyatskiy, Zaid Harchaoui, Joshua Cutler, 2021, ArXiv.

Foundations of Gauge and Perspective Duality

Dmitriy Drusvyatskiy, Michael P. Friedlander, Aleksandr Y. Aravkin, 2017, SIAM J. Optim..

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

D. Drusvyatskiy, Joshua Cutler, Zaïd Harchaoui, 2021, NeurIPS.

Local Linear Convergence for Inexact Alternating Projections on Nonconvex Sets

A. Lewis, D. Drusvyatskiy, 2019, Vietnam Journal of Mathematics.

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

Dmitriy Drusvyatskiy, Damek Davis, Liwei Jiang, 2021, ArXiv.

High probability guarantees for stochastic convex optimization

Damek Davis, D. Drusvyatskiy, 2020, COLT.

Coordinate Shadows of Semidefinite and Euclidean Distance Matrices

Dmitriy Drusvyatskiy, Henry Wolkowicz, Gábor Pataki, 2014, SIAM J. Optim..

Variable projection for nonsmooth models

Dmitriy Drusvyatskiy, Tristan van Leeuwen, Aleksandr Aravkin, 2016, 1601.05011.

Improved Rates for Derivative Free Gradient Play in Strongly Monotone Games∗

L. Ratliff, D. Drusvyatskiy, Maryam Fazel, 2021, 2022 IEEE 61st Conference on Decision and Control (CDC).

Learning in Stochastic Monotone Games with Decision-Dependent Data

L. Ratliff, D. Drusvyatskiy, Evan Faulkner, 2022, AISTATS.

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

D. Drusvyatskiy, Nathan Krislock, Henry Wolkowicz, 2014, SIAM J. Optim..

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

Rekha R. Thomas, D. Drusvyatskiy, Hon-leung Lee, 2015, SIAM Journal on Matrix Analysis and Applications.

Linear Recursive Feature Machines provably recover low-rank matrices

D. Drusvyatskiy, Adityanarayanan Radhakrishnan, Misha Belkin, 2024, ArXiv.

Trajectory length of the tame sweeping process

A. Daniilidis, D. Drusvyatskiy, 2014 .

Orbits of Geometric Descent

A. Lewis, A. Daniilidis, D. Drusvyatskiy, 2013, Canadian Mathematical Bulletin.

SIAG on Optimization Views and News

D. Drusvyatskiy, Yasmine Beck, Ivana Ljubić, 2022 .