Imagen de Portada

Learning safety critics via a non-contractive binary bellman operator

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Castellano, Agustin, Min, Hancheng, Bazerque, Juan Andrés, Mallada, Enrique
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Systems and Control
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Understanding Incremental Learning with Closed-form Solution to Gradient Flow on Overparamerterized Matrix Factorization
por: Min, Hancheng, et al.
Publicado: (2025)

Learning Reachability of Energy Storage Arbitrage
por: Tapia, Tomás, et al.
Publicado: (2025)

Symplectic Inductive Bias for Data-Driven Target Reachability in Hamiltonian Systems
por: Ouyang, Zhuo, et al.
Publicado: (2026)

Data-driven Acceleration of MPC with Guarantees
por: Castellano, Agustin, et al.
Publicado: (2025)

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models
por: Xu, Ziqing, et al.
Publicado: (2025)

Multi-agent assignment via state augmented reinforcement learning
por: Agorio, Leopoldo, et al.
Publicado: (2024)

Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization
por: Min, Hancheng, et al.
Publicado: (2023)

Data-driven Practical Stabilization of Nonlinear Systems via Chain Policies: Sample Complexity and Incremental Learning
por: Siegelmann, Roy, et al.
Publicado: (2025)

Safety-Critical Control via Recurrent Tracking Functions
por: Liu, Jixian, et al.
Publicado: (2025)

Approximate non-linear model predictive control with safety-augmented neural networks
por: Hose, Henrik, et al.
Publicado: (2023)

AoI-Aware Task Offloading and Transmission Optimization for Industrial IoT Networks: A Branching Deep Reinforcement Learning Approach
por: Chen, Yuang, et al.
Publicado: (2025)

Graph Neural Networks in Wind Power Forecasting
por: Castellano, Javier, et al.
Publicado: (2025)

Recurrent Control Barrier Functions: A Path Towards Nonparametric Safety Verification
por: Liu, Jixian, et al.
Publicado: (2025)

Cooperative Multi-Agent Assignment over Stochastic Graphs via Constrained Reinforcement Learning
por: Agorio, Leopoldo, et al.
Publicado: (2025)

ORFit: One-Pass Learning via Bridging Orthogonal Gradient Descent and Recursive Least-Squares
por: Min, Youngjae, et al.
Publicado: (2022)

Dissipative Gradient Descent Ascent Method: A Control Theory Inspired Algorithm for Min-max Optimization
por: Zheng, Tianqi, et al.
Publicado: (2024)

Stabilization of nonlinear systems with unknown delays via delay-adaptive neural operator approximate predictors
por: Bhan, Luke, et al.
Publicado: (2025)

Beyond the Neural Fog: Interpretable Learning for AC Optimal Power Flow
por: Pineda, Salvador, et al.
Publicado: (2024)

Koopman operator for time-dependent reliability analysis
por: N., Navaneeth, et al.
Publicado: (2022)

Offline Reinforcement Learning via Inverse Optimization
por: Dimanidis, Ioannis, et al.
Publicado: (2025)

Delay compensation of multi-input distinct delay nonlinear systems via neural operators
por: Bajraktari, Filip, et al.
Publicado: (2025)

Fault Detection and Identification Using a Novel Process Decomposition Algorithm for Distributed Process Monitoring
por: Villagomez, Enrique Luna, et al.
Publicado: (2024)

Offline Hierarchical Reinforcement Learning via Inverse Optimization
por: Schmidt, Carolin, et al.
Publicado: (2024)

Finite-sample guarantees for data-driven forward-backward operator methods
por: Fabiani, Filippo, et al.
Publicado: (2025)

Adaptive Federated Learning via Dynamical System Model
por: Agarwal, Aayushya, et al.
Publicado: (2025)

Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method
por: Caldarelli, Edoardo, et al.
Publicado: (2024)

Invertibility of Discrete-Time Linear Systems with Sparse Inputs
por: Poe, Kyle, et al.
Publicado: (2024)

DADEE: Well-calibrated uncertainty quantification in neural networks for barriers-based robot safety
por: Ataei, Masoud, et al.
Publicado: (2024)

Verifying Closed-Loop Contractivity of Learning-Based Controllers via Partitioning
por: Davydov, Alexander
Publicado: (2025)

Transfer Learning for Control Systems via Neural Simulation Relations
por: Nadali, Alireza, et al.
Publicado: (2024)

Neural Collapse under Gradient Flow on Shallow ReLU Networks for Orthogonally Separable Data
por: Min, Hancheng, et al.
Publicado: (2025)

Robo-taxi Fleet Coordination at Scale via Reinforcement Learning
por: Tresca, Luigi, et al.
Publicado: (2025)

Guaranteeing Control Requirements via Reward Shaping in Reinforcement Learning
por: De Lellis, Francesco, et al.
Publicado: (2023)

Restarted contractive operators to learn at equilibrium
por: Davy, Leo, et al.
Publicado: (2025)

Toward Scalable SDN for LEO Mega-Constellations: A Graph Learning Approach
por: Krishnan, Sivaram, et al.
Publicado: (2026)

Interpretable Imitation Learning via Generative Adversarial STL Inference and Control
por: Liu, Wenliang, et al.
Publicado: (2024)

Learning and Current Prediction of PMSM Drive via Differential Neural Networks
por: Mei, Wenjie, et al.
Publicado: (2024)

Accelerating Reinforcement Learning for Wind Farm Control via Expert Demonstrations
por: Nilsen, Marcus Binder, et al.
Publicado: (2026)

KKL Observer Synthesis for Nonlinear Systems via Physics-Informed Learning
por: Niazi, M. Umar B., et al.
Publicado: (2025)

Improving Stochastic Action-Constrained Reinforcement Learning via Truncated Distributions
por: Stolz, Roland, et al.
Publicado: (2025)