Chuangchuang Sun

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 41

Top Topics

Convex Programming

Reinforcement Learning

Alternating Direction Method Of Multipliers

Top Venues

IEEE Trans. Control. Netw. Syst.

Publications

Andres Arias, Chuangchuang Sun
Multi-Task Learning for Few-Shot Online Adaptation under Signal Temporal Logic Specifications. CoRR (2024)
Minjae Cho, Chuangchuang Sun
Sparsity-based Safety Conservatism for Constrained Offline Reinforcement Learning. CoRR (2024)
Minjae Cho, Jonathan P. How, Chuangchuang Sun
Out-of-Distribution Adaptation in Offline RL: Counterfactual Reasoning via Causal Normalizing Flows. CoRR (2024)
Sungwook Yang, Chaoying Pei, Ran Dai, Chuangchuang Sun
Towards an Adaptable and Generalizable Optimization Engine in Decision and Control: A Meta Reinforcement Learning Approach. CoRR (2024)
Minjae Cho, Chuangchuang Sun
Constrained Meta-Reinforcement Learning for Adaptable Safety Guarantee with Differentiable Convex Programming. AAAI (2024)
Alaa Eddine Chriat, Chuangchuang Sun
Distributionally Safe Reinforcement Learning under Model Uncertainty: A Single-Level Approach by Differentiable Convex Programming. CoRR (2023)
Minjae Cho, Chuangchuang Sun
Constrained Meta-Reinforcement Learning for Adaptable Safety Guarantee with Differentiable Convex Programming. CoRR (2023)
Alaa Eddine Chriat, Chuangchuang Sun
On the Optimality, Stability, and Feasibility of Control Barrier Functions: An Adaptive Learning-Based Approach. CoRR (2023)
Chaoying Pei, Sixiong You, Chuangchuang Sun, Ran Dai
Distributed Optimization for Rank-Constrained Semidefinite Programs. IEEE Control. Syst. Lett. 7 (2023)
Alaa Eddine Chriat, Chuangchuang Sun
On the Optimality, Stability, and Feasibility of Control Barrier Functions: An Adaptive Learning-Based Approach. IEEE Robotics Autom. Lett. 8 (11) (2023)
Alaa Eddine Chriat, Chuangchuang Sun
Wasserstein Distributionally Robust Control Barrier Function using Conditional Value-at-Risk with Differentiable Convex Programming. CoRR (2023)
Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P. How
Influencing Long-Term Behavior in Multiagent Reinforcement Learning. NeurIPS (2022)
Salomón Wollenstein-Betech, Chuangchuang Sun, Jing Zhang, Christos G. Cassandras, Ioannis Ch. Paschalidis
Joint Data-Driven Estimation of Origin-Destination Demand and Travel Latency Functions in Multiclass Transportation Networks. IEEE Trans. Control. Netw. Syst. 9 (4) (2022)
Chuangchuang Sun
An efficient approach for nonconvex semidefinite optimization via customized alternating direction method of multipliers. CoRR (2022)
Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How
ROMAX: Certifiably Robust Deep Multiagent Reinforcement Learning via Convex Relaxation. ICRA (2022)
Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P. How
Influencing Long-Term Behavior in Multiagent Reinforcement Learning. CoRR (2022)
Michael Everett, Golnaz Habibi, Chuangchuang Sun, Jonathan P. How
Reachability Analysis of Neural Feedback Loops. IEEE Access 9 (2021)
Aris Kanellopoulos, Filippos Fotiadis, Chuangchuang Sun, Zhe Xu, Kyriakos G. Vamvoudakis, Ufuk Topcu, Warren E. Dixon
Temporal-Logic-Based Intermittent, Optimal, and Safe Continuous-Time Learning for Trajectory Tracking. CDC (2021)
Aris Kanellopoulos, Filippos Fotiadis, Chuangchuang Sun, Zhe Xu, Kyriakos G. Vamvoudakis, Ufuk Topcu, Warren E. Dixon
Temporal-Logic-Based Intermittent, Optimal, and Safe Continuous-Time Learning for Trajectory Tracking. CoRR (2021)
Dong-Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan P. How
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning. ICML (2021)
Michael Everett, Golnaz Habibi, Chuangchuang Sun, Jonathan P. How
Reachability Analysis of Neural Feedback Loops. CoRR (2021)
Chuangchuang Sun, Nathaniel Kingry, Ran Dai
A Unified Formulation and Nonconvex Optimization Method for Mixed-Type Decision-Making of Robotic Systems. IEEE Trans. Robotics 37 (3) (2021)
Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How
FISAR: Forward Invariant Safe Reinforcement Learning with a Deep Neural Network-Based Optimizer. ICRA (2021)
Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How
ROMAX: Certifiably Robust Deep Multiagent Reinforcement Learning via Convex Relaxation. CoRR (2021)
Chuangchuang Sun, Shirantha Welikala, Christos G. Cassandras
Optimal Composition of Heterogeneous Multi-Agent Teams for Coverage Problems with Performance Bound Guarantees. CoRR (2020)
Dong-Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan P. How
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning. CoRR (2020)
Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How
Set-Invariant Constrained Reinforcement Learning with a Meta-Optimizer. CoRR (2020)
Chuangchuang Sun, Kyriakos G. Vamvoudakis
Continuous-Time Safe Learning with Temporal Logic Constraints in Adversarial Environments. ACC (2020)
Chuangchuang Sun, Macheng Shen, Jonathan P. How
Scaling Up Multiagent Reinforcement Learning for Robotic Systems: Learn an Adaptive Sparse Communication Graph. CoRR (2020)
Chuangchuang Sun, Xiao Li, Calin Belta
Automata Guided Semi-Decentralized Multi-Agent Reinforcement Learning. ACC (2020)
Chuangchuang Sun, Macheng Shen, Jonathan P. How
Scaling Up Multiagent Reinforcement Learning for Robotic Systems: Learn an Adaptive Sparse Communication Graph. IROS (2020)
Chuangchuang Sun, Shirantha Welikala, Christos G. Cassandras
Optimal composition of heterogeneous multi-agent teams for coverage problems with performance bound guarantees. Autom. 117 (2020)
Salomón Wollenstein-Betech, Chuangchuang Sun, Jing Zhang, Ioannis Ch. Paschalidis
Joint Estimation of OD Demands and Cost Functions in Transportation Networks from Data. CoRR (2019)
Chuangchuang Sun, Ran Dai
An Iterative Rank Penalty Method for Nonconvex Quadratically Constrained Quadratic Programs. SIAM J. Control. Optim. 57 (6) (2019)
Salomón Wollenstein-Betech, Chuangchuang Sun, Jing Zhang, Ioannis Ch. Paschalidis
Joint Estimation of OD Demands and Cost Functions in Transportation Networks from Data. CDC (2019)
Chuangchuang Sun, Ran Dai
An Efficient Module Detection Algorithm for Large-Scale Complex Networks. ACC (2018)
Chuangchuang Sun, Ran Dai
Distributed Optimization for Convex Mixed-Integer Programs based on Projected Subgradient Algorithm. CDC (2018)
Chuangchuang Sun, Ran Dai, Mehran Mesbahi
Weighted Network Design With Cardinality Constraints via Alternating Direction Method of Multipliers. IEEE Trans. Control. Netw. Syst. 5 (4) (2018)
Chuangchuang Sun, Ran Dai
A customized ADMM for rank-constrained optimization problems with approximate formulations. CDC (2017)
Chuangchuang Sun, Ran Dai
A decomposition method for nonconvex quadratically constrained quadratic programs. ACC (2017)
Chuangchuang Sun, Ran Dai
Rank-constrained optimization and its applications. Autom. 82 (2017)
Chuangchuang Sun, Ran Dai
An iterative approach to Rank Minimization Problems. CDC (2015)
Chuangchuang Sun, Ran Dai
Identification of network topology via quadratic optimization. ACC (2015)
Yue Zu, Chuangchuang Sun, Ran Dai
Distributed estimation for spatial rigid motion based on dual quaternions. CDC (2014)
Dangxiao Wang, Jing Guo, Chuangchuang Sun, Mu Xu, Yuru Zhang
A Flexible Concept for Designing Multiaxis Force/Torque Sensors Using Force Closure Theorem. IEEE Trans. Instrum. Meas. 62 (7) (2013)