Drusvyatskiy, Dmitriy

15 publications

ICML 2025 Finite-Time Convergence Rates in Stochastic Stackelberg Games with Smooth Algorithmic Agents Eric Frankel, Kshitij Kulkarni, Dmitriy Drusvyatskiy, Sewoong Oh, Lillian J. Ratliff

COLT 2025 Online Covariance Estimation in Nonsmooth Stochastic Approximation Liwei Jiang, Abhishek Roy, Krishnakumar Balasubramanian, Damek Davis, Dmitriy Drusvyatskiy, Sen Na

JMLR 2024 Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality Joshua Cutler, Mateo Díaz, Dmitriy Drusvyatskiy

NeurIPS 2023 Aiming Towards the Minimizers: Fast Convergence of SGD for Overparametrized Problems Chaoyue Liu, Dmitriy Drusvyatskiy, Misha Belkin, Damek Davis, Yian Ma

JMLR 2023 Multiplayer Performative Prediction: Learning in Decision-Dependent Games Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff

NeurIPSW 2023 SGD Batch Saturation for Training Wide Neural Networks Chaoyue Liu, Dmitriy Drusvyatskiy, Mikhail Belkin, Damek Davis, Yian Ma

JMLR 2023 Stochastic Optimization Under Distributional Drift Joshua Cutler, Dmitriy Drusvyatskiy, Zaid Harchaoui

AISTATS 2022 Learning in Stochastic Monotone Games with Decision-Dependent Data Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian Ratliff

NeurIPS 2022 A Gradient Sampling Method with Complexity Guarantees for Lipschitz Functions in High and Low Dimensions Damek Davis, Dmitriy Drusvyatskiy, Yin Tat Lee, Swati Padmanabhan, Guanghao Ye

AAAI 2022 Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments Mitas Ray, Lillian J. Ratliff, Dmitriy Drusvyatskiy, Maryam Fazel

JMLR 2021 From Low Probability to High Confidence in Stochastic Convex Optimization Damek Davis, Dmitriy Drusvyatskiy, Lin Xiao, Junyu Zhang

NeurIPS 2021 Stochastic Optimization Under Time Drift: Iterate Averaging, Step-Decay Schedules, and High Probability Guarantees Joshua Cutler, Dmitriy Drusvyatskiy, Zaid Harchaoui

COLT 2020 High Probability Guarantees for Stochastic Convex Optimization Damek Davis, Dmitriy Drusvyatskiy

ICML 2019 Iterative Linearized Control: Stable Algorithms and Complexity Guarantees Vincent Roulet, Siddhartha Srinivasa, Dmitriy Drusvyatskiy, Zaid Harchaoui

AISTATS 2018 Catalyst for Gradient-Based Nonconvex Optimization Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy, Julien Mairal, Zaïd Harchaoui