Papers
546 papers found
Data-driven Control of Unknown Linear Systems via Quantized Feedback
Feiran Zhao, Xingchen Li, Keyou You
Data-Driven Safety Verification of Stochastic Systems via Barrier Certificates: A Wait-and-Judge Approach
Ali Salamati, Majid Zamani
Data-Enabled Gradient Flow as Feedback Controller: Regulation of Linear Dynamical Systems to Minimizers of Unknown Functions
Liliaokeawawa Cothren, Gianluca Bianchin, Emiliano Dall’Anese
Deep Interactive Motion Prediction and Planning: Playing Games with Motion Prediction Models
Jose Luis Vazquez Espinoza, Alexander Liniger, Wilko Schwarting et al.
Diffeomorphic Transforms for Generalised Imitation Learning
Weiming Zhi, Tin Lai, Lionel Ott et al.
Distributed Control using Reinforcement Learning with Temporal-Logic-Based Reward Shaping
Ningyuan Zhang, Wenliang Liu, Calin Belta
Distributed Neural Network Control with Dependability Guarantees: a Compositional Port-Hamiltonian Approach
Luca Furieri, Clara Lucía Galimberti, Muhammad Zakwan et al.
Distributed Stochastic Nash Equilibrium Learning in Locally Coupled Network Games with Unknown Parameters
Yuanhanqing Huang, Jianghai Hu
Dynamic Learning of Correlation Potentials for a Time-Dependent Kohn-Sham System
Harish S. Bhat, Kevin Collins, Prachi Gupta et al.
Experience Replay with Likelihood-free Importance Weights
Samarth Sinha, Jiaming Song, Animesh Garg et al.
Formal Synthesis of Safety Controllers for Unknown Stochastic Control Systems using Gaussian Process Learning
Rameez Wajid, Asad Ullah Awan, Majid Zamani
Generalization Bounded Implicit Learning of Nearly Discontinuous Functions
Bibit Bianchini, Mathew Halm, Nikolai Matni et al.
Gradient and Projection Free Distributed Online Min-Max Resource Optimization
Jingrong Wang, Ben Liang
Improving Dynamic Regret in Distributed Online Mirror Descent Using Primal and Dual Information
Nima Eshraghi, Ben Liang
Input-to-State Stable Neural Ordinary Differential Equations with Applications to Transient Modeling of Circuits
Alan Yang, Jie Xiong, Maxim Raginsky et al.
i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery
Cameron R. Wolfe, Anastasios Kyrillidis
Joint Synthesis of Safety Certificate and Safe Control Policy Using Constrained Reinforcement Learning
Haitong Ma, Changliu Liu, Shengbo Eben Li et al.
Learning-based Moving Horizon Estimation through Differentiable Convex Optimization Layers
Simon Muntwiler, Kim P. Wabersich, Melanie N. Zeilinger
Learning-Enabled Robust Control with Noisy Measurements
Olle Kjellqvist, Anders Rantzer
Learning Linear Complementarity Systems
Wanxin Jin, Alp Aydinoglu, Mathew Halm et al.
Learning Linear Models Using Distributed Iterative Hessian Sketching
Han Wang, James Anderson
Learning POMDP Models with Similarity Space Regularization: a Linear Gaussian Case Study
Yujie Yang, Jianyu Chen, Shengbo Li
Learning Reversible Symplectic Dynamics
Riccardo Valperga, Kevin Webster, Dmitry Turaev et al.
Learning Spatio-Temporal Specifications for Dynamical Systems
Suhail Alsalehi, Erfan Aasi, Ron Weiss et al.