Identification of surface tension in mean curvature flow. - Insoon Yang; Claire J. Tomlin (ACC, 2013)

Infinitesimal interconnection variation in nonlinear networked systems. - Insoon Yang; Samuel Burden; S. Shankar Sastry; Claire J. Tomlin (CDC, 2013)

Regularization-based identification for level set equations. - Insoon Yang; Claire J. Tomlin (CDC, 2013)

One-shot computation of reachable sets for differential games. - Insoon Yang; Sabine Becker-Weimann; Mina J. Bissell; Claire J. Tomlin (HSCC, 2013)

Direct load control for electricity market risk management via risk-limiting dynamic contracts. - Insoon Yang; Duncan S. Callaway; Claire J. Tomlin (Allerton, 2014)

Dynamic contracts with partial observations: Application to indirect load control. - Insoon Yang; Duncan S. Callaway; Claire J. Tomlin (ACC, 2014)

Utility learning model predictive control for personal electric loads. - Insoon Yang; Melanie Nicole Zeilinger; Claire J. Tomlin (CDC, 2014)

Reaction-diffusion systems in protein networks: Global existence and identification. - Insoon Yang; Claire J. Tomlin (Syst. Control. Lett., 2014)

Indirect load control for electricity market risk management via risk-limiting dynamic contracts. - Insoon Yang; Duncan S. Callaway; Claire J. Tomlin (ACC, 2015)

Optimal Dynamic Contracts for a Large-Scale Principal-Agent Hierarchy: A Concavity-Preserving Approach. - Christopher W. Miller; Insoon Yang (CoRR, 2015)

Reducing electricity price volatility via stochastic storage control. - Insoon Yang; Asuman E. Ozdaglar (ACC, 2016)

Submodularity of energy storage placement in power networks. - Junjie Qin; Insoon Yang; Ram Rajagopal (CDC, 2016)

Control of Supermarket Refrigeration Systems via Online Combinatorial Optimization. - Insoon Yang; Sila Kiliccote; Ram Rajagopal; Claire J. Tomlin (CoRR, 2016)

Approximation Algorithms for Optimization of Combinatorial Dynamical Systems. - Insoon Yang; Samuel A. Burden; Ram Rajagopal; S. Shankar Sastry; Claire J. Tomlin (IEEE Trans. Autom. Control., 2016)

Data-driven distributionally robust control of energy storage to manage wind power fluctuations. - Samantha Samuelson; Insoon Yang (CCTA, 2017)

Distributionally robust stochastic control with conic confidence sets. - Insoon Yang (CDC, 2017)

A Convex Optimization Approach to Distributionally Robust Markov Decision Processes With Wasserstein Distance. - Insoon Yang (IEEE Control. Syst. Lett., 2017)

Optimal Control of Conditional Value-at-Risk in Continuous Time. - Christopher W. Miller; Insoon Yang (SIAM J. Control. Optim., 2017)

Variance-Constrained Risk Sharing in Stochastic Systems. - Insoon Yang; Duncan S. Callaway; Claire J. Tomlin (IEEE Trans. Autom. Control., 2017)

Safety-Aware Optimal Control of Stochastic Systems Using Conditional Value-at-Risk. - Samantha Samuelson; Insoon Yang (ACC, 2018)

A dynamic game approach to distributionally robust safety specifications for stochastic systems. - Insoon Yang (Autom., 2018)

Stochastic Subgradient Methods for Dynamic Programming in Continuous State and Action Spaces. - Sunho Jang; Insoon Yang (CDC, 2019)

On Improving the Robustness of Reinforcement Learning-based Controllers using Disturbance Observer. - Jeong Woo Kim; Hyungbo Shim; Insoon Yang (CDC, 2019)

Sample Efficient Home Power Anomaly Detection in Real Time Using Semi-Supervised Learning. - Xinlin Wang; Insoon Yang; Sung-Hoon Ahn (IEEE Access, 2019)

Risk-Aware Motion Planning and Control Using CVaR-Constrained Optimization. - Astghik Hakobyan; Gyeong Chan Kim; Insoon Yang (IEEE Robotics Autom. Lett., 2019)

Submodularity of Storage Placement Optimization in Power Networks. - Junjie Qin; Insoon Yang; Ram Rajagopal (IEEE Trans. Autom. Control., 2019)

A Stochastic Consensus Method for Nonconvex Optimization on the Stiefel Manifold. - Jeongho Kim 002; Myeongju Kang; Dohyun Kim; Seung-Yeal Ha; Insoon Yang (CDC, 2020)

Minimax Control of Ambiguous Linear Stochastic Systems Using the Wasserstein Metric. - Kihyun Kim 001; Insoon Yang (CDC, 2020)

Wasserstein Distributionally Robust Motion Planning and Control with Safety Constraints Using Conditional Value-at-Risk. - Astghik Hakobyan; Insoon Yang (ICRA, 2020)

STAR: Spatio-Temporal Prediction of Air Quality Using a Multimodal Approach. - Tien-Cuong Bui; Joonyoung Kim; Taewoo Kang; Donghyeon Lee; Junyoung Choi; Insoon Yang; Kyomin Jung; Sang-Kyun Cha (IntelliSys (2), 2020)

Learning-Based Distributionally Robust Motion Control with Gaussian Processes. - Astghik Hakobyan; Insoon Yang (IROS, 2020)

Hamilton-Jacobi-Bellman Equations for Q-Learning in Continuous Time. - Jeongho Kim 002; Insoon Yang (L4DC, 2020)

A3DQN: Adaptive Anderson Acceleration for Deep Q-Networks. - Melike Ermis; Insoon Yang (SSCI, 2020)

Multi-Objective Predictive Taxi Dispatch via Network Flow Optimization. - Beomjun Kim; Jeongho Kim 002; Subin Huh; Seungil You; Insoon Yang (IEEE Access, 2020)

Safe reinforcement learning for probabilistic reachability and safety specifications: A Lyapunov-based approach. - Subin Huh; Insoon Yang (CoRR, 2020)

Hamilton-Jacobi-Bellman Equations for Maximum Entropy Optimal Control. - Jeongho Kim 002; Insoon Yang (CoRR, 2020)

A Convex Optimization Approach to Dynamic Programming in Continuous State and Action Spaces. - Insoon Yang (J. Optim. Theory Appl., 2020)

On Anderson Acceleration for Partially Observable Markov Decision Processes. - Melike Ermis; Mingyu Park; Insoon Yang (CDC, 2021)

Toward Improving the Distributional Robustness of Risk-Aware Controllers in Learning-Enabled Environments. - Astghik Hakobyan; Insoon Yang (CDC, 2021)

Training Wasserstein GANs without gradient penalties. - Dohyun Kwon 002; Yeoneung Kim; Guido Montúfar; Insoon Yang (CoRR, 2021)

Hamilton-Jacobi Deep Q-Learning for Deterministic Continuous-Time Systems with Lipschitz Continuous Controls. - Jeongho Kim 002; Jaeuk Shin; Insoon Yang (J. Mach. Learn. Res., 2021)

Wasserstein Distributionally Robust Stochastic Control: A Data-Driven Approach. - Insoon Yang (IEEE Trans. Autom. Control., 2021)

On Affine Policies for Wasserstein Distributionally Robust Unit Commitment. - Youngchae Cho; Insoon Yang (CDC, 2022)

Wasserstein Distributionally Robust Control of Partially Observable Linear Systems: Tractable Approximation and Performance Guarantee. - Astghik Hakobyan; Insoon Yang (CDC, 2022)

Accelerated Gradient Methods for Geodesically Convex Optimization: Tractable Algorithms and Convergence Analysis. - Jungbin Kim; Insoon Yang (ICML, 2022)

Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs. - Yeoneung Kim; Insoon Yang; Kwang-Sung Jun (NeurIPS, 2022)

On representation formulas for optimal control: A Lagrangian perspective. - Yeoneung Kim; Insoon Yang (CoRR, 2022)

Infusing Model Predictive Control Into Meta-Reinforcement Learning for Mobile Robots in Dynamic Environments. - Jaeuk Shin; Astghik Hakobyan; Mingyu Park; Yeoneung Kim; Gihun Kim; Insoon Yang (IEEE Robotics Autom. Lett., 2022)

Risk-Sensitive Safety Analysis Using Conditional Value-at-Risk. - Margaret P. Chapman; Riccardo Bonalli; Kevin M. Smith; Insoon Yang; Marco Pavone 001; Claire J. Tomlin (IEEE Trans. Autom. Control., 2022)

Wasserstein Distributionally Robust Motion Control for Collision Avoidance Using Conditional Value-at-Risk. - Astghik Hakobyan; Insoon Yang (IEEE Trans. Robotics, 2022)

Data-Driven Stochastic Optimization Using Upper Confidence Bounds: Performance Guarantees and Distributional Robustness. - Youngchae Cho; Insoon Yang (CDC, 2023)

On Concentration Bounds for Bayesian Identification of Linear Non-Gaussian Systems. - Yeoneung Kim; Gihun Kim; Insoon Yang (CDC, 2023)

Unifying Nesterov's Accelerated Gradient Methods for Convex and Strongly Convex Objective Functions. - Jungbin Kim; Insoon Yang (ICML, 2023)

Distributionally Robust Optimization with Unscented Transform for Learning-Based Motion Control in Dynamic Environments. - Astghik Hakobyan; Insoon Yang (ICRA, 2023)

Convergence analysis of ODE models for accelerated first-order methods via positive semidefinite kernels. - Jungbin Kim; Insoon Yang (NeurIPS, 2023)

Using affine policies to reformulate two-stage Wasserstein distributionally robust linear programs to be independent of sample size. - Youngchae Cho; Insoon Yang (CoRR, 2023)

On Task-Relevant Loss Functions in Meta-Reinforcement Learning and Online LQR. - Jaeuk Shin; Giho Kim; Howon Lee; Joonho Han; Insoon Yang (CoRR, 2023)

Distributionally Robust Differential Dynamic Programming With Wasserstein Distance. - Astghik Hakobyan; Insoon Yang (IEEE Control. Syst. Lett., 2023)

Maximum Entropy Optimal Control of Continuous-Time Dynamical Systems. - Jeongho Kim 002; Insoon Yang (IEEE Trans. Autom. Control., 2023)

Distributionally Robust Risk Map for Learning-Based Motion Planning and Control: A Semidefinite Programming Approach. - Astghik Hakobyan; Insoon Yang (IEEE Trans. Robotics, 2023)

Distributional Robustness in Minimax Linear Quadratic Control with Wasserstein Distance. - Kihyun Kim 001; Insoon Yang (SIAM J. Control. Optim., 2023)

On task-relevant loss functions in meta-reinforcement learning. - Jaeuk Shin; Giho Kim; Howon Lee; Joonho Han; Insoon Yang (L4DC, 2024)

Anderson acceleration for partially observable Markov decision processes: A maximum entropy approach. - Mingyu Park; Jaeuk Shin; Insoon Yang (Autom., 2024)

Approximate Thompson Sampling for Learning Linear Quadratic Regulators with O(√T) Regret. - Yeoneung Kim; Gihun Kim; Insoon Yang (CoRR, 2024)

Wasserstein Distributionally Robust Control and State Estimation for Partially Observable Linear Systems. - Minhyuk Jang; Astghik Hakobyan; Insoon Yang (CoRR, 2024)

Generalized Continuous-Time Models for Nesterov's Accelerated Gradient Methods. - Chanwoong Park; Youngchae Cho; Insoon Yang (CoRR, 2024)

Wasserstein Distributionally Robust Regret Minimization. - Youngchae Cho; Insoon Yang (IEEE Control. Syst. Lett., 2024)

Multiparametric Analysis of Multi-Task Markov Decision Processes: Structure, Invariance, and Reducibility. - Jaeuk Shin; Insoon Yang (IEEE Control. Syst. Lett., 2024)

Risk-Aware Wasserstein Distributionally Robust Control of Vessels in Natural Waterways. - Juan Moreno Nadales; Astghik Hakobyan; David Muñoz de la Peña; Daniel Limón; Insoon Yang (IEEE Trans. Control. Syst. Technol., 2024)

Wasserstein Distributionally Robust Control of Partially Observable Linear Stochastic Systems. - Astghik Hakobyan; Insoon Yang (IEEE Trans. Autom. Control., 2024)

Control of Fab Lifters via Deep Reinforcement Learning: A Semi-MDP Approach. - Giho Kim; Jaeuk Shin; Gihun Kim; Joonrak Kim; Insoon Yang (IEEE Trans Autom. Sci. Eng., 2024)

Approximate Thompson Sampling for Learning Linear Quadratic Regulators with $O( sqrt{T})$ Regret. - Yeoneung Kim; Gihun Kim; Jiwhan Park; Insoon Yang (L4DC, 2025)

On the Steady-State Distributionally Robust Kalman Filter. - Minhyuk Jang; Astghik Hakobyan; Insoon Yang (CoRR, 2025)

Robust Continuous-Time Generation Scheduling under Power Demand Uncertainty: An Affine Decision Rule Approach. - Youngchae Cho; Insoon Yang; Takayuki Ishizaki (CoRR, 2025)

Egocentric Conformal Prediction for Safe and Efficient Navigation in Dynamic Cluttered Environments. - Jaeuk Shin; Jungjin Lee; Insoon Yang (CoRR, 2025)