Convergence analysis and performance of an extended central force optimization algorithm. - Dongsheng Ding; Donglian Qi; Xiaoping Luo; Jinfei Chen; Xuejie Wang; Pengying Du (Appl. Math. Comput., 2012)

Adaptive Mittag-Leffler stabilization of commensurate fractional-order nonlinear systems. - Dongsheng Ding; Donglian Qi; Yao Meng; Li Xu (CDC, 2014)

A primal-dual laplacian gradient flow dynamics for distributed resource allocation problems. - Dongsheng Ding; Mihailo R. Jovanovic (ACC, 2018)

An Exponentially Convergent Primal-Dual Algorithm for Nonsmooth Composite Minimization. - Dongsheng Ding; Bin Hu; Neil K. Dhingra; Mihailo R. Jovanovic (CDC, 2018)

Global exponential stability of primal-dual gradient flow dynamics based on the proximal augmented Lagrangian. - Dongsheng Ding; Mihailo R. Jovanovic (ACC, 2019)

Distributed robust statistical learning: Byzantine mirror descent. - Dongsheng Ding; Xiaohan Wei; Mihailo R. Jovanovic (CDC, 2019)

Fast Multi-Agent Temporal-Difference Learning via Homotopy Stochastic Primal-Dual Optimization. - Dongsheng Ding; Xiaohan Wei; Zhuoran Yang; Zhaoran Wang 001; Mihailo R. Jovanovic (CoRR, 2019)

Global exponential stability of primal-dual gradient flow dynamics based on the proximal augmented Lagrangian: A Lyapunov-based approach. - Dongsheng Ding; Mihailo R. Jovanovic (CDC, 2020)

Natural Policy Gradient Primal-Dual Method for Constrained Markov Decision Processes. - Dongsheng Ding; Kaiqing Zhang; Tamer Basar; Mihailo R. Jovanovic (NeurIPS, 2020)

Provably Efficient Safe Exploration via Primal-Dual Policy Optimization. - Dongsheng Ding; Xiaohan Wei; Zhuoran Yang; Zhaoran Wang 001; Mihailo R. Jovanovic (AISTATS, 2021)

Byzantine-resilient distributed learning under constraints. - Dongsheng Ding; Xiaohan Wei; Hao Yu 002; Mihailo R. Jovanovic (ACC, 2021)

Discounted online Newton method for time-varying time series prediction. - Dongsheng Ding; Jianjun Yuan; Mihailo R. Jovanovic (ACC, 2021)

Convergence and optimality of policy gradient primal-dual method for constrained Markov decision processes. - Dongsheng Ding; Kaiqing Zhang; Tamer Basar; Mihailo R. Jovanovic (ACC, 2022)

Policy gradient primal-dual mirror descent for constrained MDPs with large state spaces. - Dongsheng Ding; Mihailo R. Jovanovic (CDC, 2022)

Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence. - Dongsheng Ding; Chen-Yu Wei; Kaiqing Zhang; Mihailo R. Jovanovic (ICML, 2022)

Convergence and sample complexity of natural policy gradient primal-dual methods for constrained MDPs. - Dongsheng Ding; Kaiqing Zhang; Jiali Duan; Tamer Basar; Mihailo R. Jovanovic (CoRR, 2022)

Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning. - Dongsheng Ding; Xiaohan Wei; Zhuoran Yang; Zhaoran Wang 001; Mihailo R. Jovanovic (L4DC, 2023)

Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs. - Dongsheng Ding; Chen-Yu Wei; Kaiqing Zhang; Alejandro Ribeiro (NeurIPS, 2023)

Resilient Constrained Reinforcement Learning. - Dongsheng Ding; Zhengyan Huan; Alejandro Ribeiro (AISTATS, 2024)

One-Shot Safety Alignment for Large Language Models via Optimal Dualization. - Xinmeng Huang; Shuo Li; Edgar Dobriban; Osbert Bastani; Hamed Hassani; Dongsheng Ding (NeurIPS, 2024)

Constrained Diffusion Models via Dual Training. - Shervin Khalafi; Dongsheng Ding; Alejandro Ribeiro (NeurIPS, 2024)

Deterministic Policy Gradient Primal-Dual Methods for Continuous-Space Constrained MDPs. - Sergio Rozada; Dongsheng Ding; Antonio G. Marques; Alejandro Ribeiro (AAAI, 2025)

Alignment of large language models with constrained learning. - Botong Zhang; Shuo Li; Ignacio Hounie; Osbert Bastani; Dongsheng Ding; Alejandro Ribeiro (CoRR, 2025)