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Chuangchuang Sun
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2020 – today
- 2024
- [c17]Minjae Cho, Chuangchuang Sun:
Constrained Meta-Reinforcement Learning for Adaptable Safety Guarantee with Differentiable Convex Programming. AAAI 2024: 20975-20983 - [i18]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 abs/2401.02508 (2024) - [i17]Minjae Cho, Jonathan P. How, Chuangchuang Sun:
Out-of-Distribution Adaptation in Offline RL: Counterfactual Reasoning via Causal Normalizing Flows. CoRR abs/2405.03892 (2024) - [i16]Minjae Cho, Chuangchuang Sun:
Sparsity-based Safety Conservatism for Constrained Offline Reinforcement Learning. CoRR abs/2407.13006 (2024) - [i15]Andres Arias, Chuangchuang Sun:
Multi-Task Learning for Few-Shot Online Adaptation under Signal Temporal Logic Specifications. CoRR abs/2407.21144 (2024) - 2023
- [j10]Chaoying Pei
, Sixiong You, Chuangchuang Sun
Distributed Optimization for Rank-Constrained Semidefinite Programs. IEEE Control. Syst. Lett. 7: 103-108 (2023) - [j9]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): 7865-7872 (2023) - [i14]Alaa Eddine Chriat, Chuangchuang Sun:
On the Optimality, Stability, and Feasibility of Control Barrier Functions: An Adaptive Learning-Based Approach. CoRR abs/2305.03608 (2023) - [i13]Alaa Eddine Chriat, Chuangchuang Sun:
Wasserstein Distributionally Robust Control Barrier Function using Conditional Value-at-Risk with Differentiable Convex Programming. CoRR abs/2309.08700 (2023) - [i12]Alaa Eddine Chriat, Chuangchuang Sun:
Distributionally Safe Reinforcement Learning under Model Uncertainty: A Single-Level Approach by Differentiable Convex Programming. CoRR abs/2310.02459 (2023) - [i11]Minjae Cho, Chuangchuang Sun:
Constrained Meta-Reinforcement Learning for Adaptable Safety Guarantee with Differentiable Convex Programming. CoRR abs/2312.10230 (2023) - 2022
- [j8]Salomón Wollenstein-Betech
Joint Data-Driven Estimation of Origin-Destination Demand and Travel Latency Functions in Multiclass Transportation Networks. IEEE Trans. Control. Netw. Syst. 9(4): 1576-1588 (2022) - [c16]Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How:
ROMAX: Certifiably Robust Deep Multiagent Reinforcement Learning via Convex Relaxation. ICRA 2022: 5503-5510 - [c15]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 - [i10]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 abs/2203.03535 (2022) - [i9]Chuangchuang Sun:
An efficient approach for nonconvex semidefinite optimization via customized alternating direction method of multipliers. CoRR abs/2209.03437 (2022) - 2021
- [j7]Michael Everett
Reachability Analysis of Neural Feedback Loops. IEEE Access 9: 163938-163953 (2021) - [j6]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): 831-846 (2021) - [c14]Aris Kanellopoulos, Filippos Fotiadis, Chuangchuang Sun, Zhe Xu, Kyriakos G. Vamvoudakis
Temporal-Logic-Based Intermittent, Optimal, and Safe Continuous-Time Learning for Trajectory Tracking. CDC 2021: 1263-1268 - [c13]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: 5541-5550 - [c12]Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How:
FISAR: Forward Invariant Safe Reinforcement Learning with a Deep Neural Network-Based Optimizer. ICRA 2021: 10617-10624 - [i8]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 abs/2104.02547 (2021) - [i7]Michael Everett, Golnaz Habibi, Chuangchuang Sun, Jonathan P. How:
Reachability Analysis of Neural Feedback Loops. CoRR abs/2108.04140 (2021) - [i6]Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How:
ROMAX: Certifiably Robust Deep Multiagent Reinforcement Learning via Convex Relaxation. CoRR abs/2109.06795 (2021) - 2020
- [j5]Chuangchuang Sun, Shirantha Welikala
Optimal composition of heterogeneous multi-agent teams for coverage problems with performance bound guarantees. Autom. 117: 108961 (2020) - [c11]Chuangchuang Sun, Xiao Li, Calin Belta:
Automata Guided Semi-Decentralized Multi-Agent Reinforcement Learning. ACC 2020: 3900-3905 - [c10]Chuangchuang Sun, Kyriakos G. Vamvoudakis
Continuous-Time Safe Learning with Temporal Logic Constraints in Adversarial Environments. ACC 2020: 4786-4791 - [c9]Chuangchuang Sun, Macheng Shen, Jonathan P. How:
Scaling Up Multiagent Reinforcement Learning for Robotic Systems: Learn an Adaptive Sparse Communication Graph. IROS 2020: 11755-11762 - [i5]Chuangchuang Sun, Macheng Shen, Jonathan P. How:
Scaling Up Multiagent Reinforcement Learning for Robotic Systems: Learn an Adaptive Sparse Communication Graph. CoRR abs/2003.01040 (2020) - [i4]Chuangchuang Sun, Shirantha Welikala, Christos G. Cassandras:
Optimal Composition of Heterogeneous Multi-Agent Teams for Coverage Problems with Performance Bound Guarantees. CoRR abs/2003.05587 (2020) - [i3]Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How:
Set-Invariant Constrained Reinforcement Learning with a Meta-Optimizer. CoRR abs/2006.11419 (2020) - [i2]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 abs/2011.00382 (2020)
2010 – 2019
- 2019
- [j4]Chuangchuang Sun
An Iterative Rank Penalty Method for Nonconvex Quadratically Constrained Quadratic Programs. SIAM J. Control. Optim. 57(6): 3749-3766 (2019) - [c8]Salomón Wollenstein-Betech
Joint Estimation of OD Demands and Cost Functions in Transportation Networks from Data. CDC 2019: 5113-5118 - [i1]Salomón Wollenstein-Betech, Chuangchuang Sun, Jing Zhang, Ioannis Ch. Paschalidis:
Joint Estimation of OD Demands and Cost Functions in Transportation Networks from Data. CoRR abs/1909.00941 (2019) - 2018
- [j3]Chuangchuang Sun
Weighted Network Design With Cardinality Constraints via Alternating Direction Method of Multipliers. IEEE Trans. Control. Netw. Syst. 5(4): 2073-2084 (2018) - [c7]Chuangchuang Sun, Ran Dai
An Efficient Module Detection Algorithm for Large-Scale Complex Networks. ACC 2018: 4153-4158 - [c6]Chuangchuang Sun, Ran Dai
Distributed Optimization for Convex Mixed-Integer Programs based on Projected Subgradient Algorithm. CDC 2018: 2581-2586 - 2017
- [j2]Chuangchuang Sun, Ran Dai
Rank-constrained optimization and its applications. Autom. 82: 128-136 (2017) - [c5]Chuangchuang Sun, Ran Dai
A decomposition method for nonconvex quadratically constrained quadratic programs. ACC 2017: 4631-4636 - [c4]Chuangchuang Sun, Ran Dai
A customized ADMM for rank-constrained optimization problems with approximate formulations. CDC 2017: 3769-3774 - 2015
- [c3]Chuangchuang Sun, Ran Dai
Identification of network topology via quadratic optimization. ACC 2015: 5752-5757 - [c2]Chuangchuang Sun, Ran Dai
An iterative approach to Rank Minimization Problems. CDC 2015: 3317-3323 - 2014
- [c1]Yue Zu, Chuangchuang Sun, Ran Dai
Distributed estimation for spatial rigid motion based on dual quaternions. CDC 2014: 334-339 - 2013
- [j1]Dangxiao Wang
A Flexible Concept for Designing Multiaxis Force/Torque Sensors Using Force Closure Theorem. IEEE Trans. Instrum. Meas. 62(7): 1951-1959 (2013)
Coauthor Index
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last updated on 2024-08-23 19:28 CEST by the dblp team
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