:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Ebrahimkhani, Sadegh, Lataire, John
Format:	Preprint
Published:	2025
Subjects:	Systems and Control Machine Learning
Online Access:	https://arxiv.org/abs/2508.01453
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Combined Estimator for Nonlinear System Identification via LPV Approximations
by: Sadegh Ebrahimkhani, et al.
Published: (2025)

Nonlinear continuous‐time system identification by linearization around a time‐varying setpoint
by: Mehrad Ghasem Sharabiany, et al.
Published: (2024)

Kernel-Based Safe Exploration in Deep Reinforcement Learning
by: Majumdar, Rupak, et al.
Published: (2026)

Kernel-Based Learning of Safety Barriers
by: Schön, Oliver, et al.
Published: (2026)

Learnable Faster Kernel-PCA for Nonlinear Fault Detection: Deep Autoencoder-Based Realization
by: Ren, Zelin, et al.
Published: (2021)

Analysis of Thompson Sampling for Controlling Unknown Linear Diffusion Processes
by: Faradonbeh, Mohamad Kazem Shirani, et al.
Published: (2022)

Kernel-Based Optimal Control: An Infinitesimal Generator Approach
by: Bevanda, Petar, et al.
Published: (2024)

A Behavioral Framework for Data-Driven Modeling of Nonlinear Systems in Vector-Valued Reproducing Kernel Hilbert Spaces
by: Hou, Boya, et al.
Published: (2026)

Control Occupation Kernel Regression for Nonlinear Control-Affine Systems
by: Abudia, Moad, et al.
Published: (2021)

Provably-Stable Neural Network-Based Control of Nonlinear Systems
by: Li, Anran, et al.
Published: (2025)

Learning Linearized Models from Nonlinear Systems under Initialization Constraints with Finite Data
by: Xin, Lei, et al.
Published: (2025)

On the Sample Complexity of Discounted Reinforcement Learning with Optimized Certainty Equivalents
by: Mortensen, Oliver, et al.
Published: (2026)

Change Detection of Markov Kernels with Unknown Pre and Post Change Kernel
by: Chen, Hao, et al.
Published: (2022)

Data-Driven Distributionally Robust Safety Verification Using Barrier Certificates and Conditional Mean Embeddings
by: Schön, Oliver, et al.
Published: (2024)

Sparse Mamba: Introducing Controllability, Observability, And Stability To Structural State Space Models
by: Hamdan, Emadeldeen, et al.
Published: (2024)

Neural Port-Hamiltonian Models for Nonlinear Distributed Control: An Unconstrained Parametrization Approach
by: Zakwan, Muhammad, et al.
Published: (2024)

Safe and High-Performance Learning of Model Predicitve Control using Kernel-Based Interpolation
by: Rose, Alexander, et al.
Published: (2024)

Towards Safe Learning-Based Non-Linear Model Predictive Control through Recurrent Neural Network Modeling
by: Clement, Mihaela-Larisa, et al.
Published: (2026)

A New Approach to Controlling Linear Dynamical Systems
by: Brahmbhatt, Anand, et al.
Published: (2025)

A Model-Based Approach to Imitation Learning through Multi-Step Predictions
by: Balim, Haldun, et al.
Published: (2025)

LUCID: Learning-Enabled Uncertainty-Aware Certification of Stochastic Dynamical Systems
by: Casablanca, Ernesto, et al.
Published: (2025)

MPC of Uncertain Nonlinear Systems with Meta-Learning for Fast Adaptation of Neural Predictive Models
by: Yan, Jiaqi, et al.
Published: (2024)

Scalable Kernel Inverse Optimization
by: Long, Youyuan, et al.
Published: (2024)

Graph Neural Network-Based Distributed Optimal Control for Linear Networked Systems: An Online Distributed Training Approach
by: Song, Zihao, et al.
Published: (2025)

Koopman Kernel Regression
by: Bevanda, Petar, et al.
Published: (2023)

Deep Dictionary-Free Method for Identifying Linear Model of Nonlinear System with Input Delay
by: Valábek, Patrik, et al.
Published: (2025)

Quasi-Newton Compatible Actor-Critic for Deterministic Policies
by: Kordabad, Arash Bahari, et al.
Published: (2025)

Koopman-Based Nonlinear Identification and Adaptive Control of a Turbofan Engine
by: Grasev, David
Published: (2026)

Kernel Mean Embedding Topology: Weak and Strong Forms for Stochastic Kernels and Implications for Model Learning
by: Saldi, Naci, et al.
Published: (2025)

Convex Hybrid Modeling: An Operator-Based Approach
by: Tang, Wentao
Published: (2026)

Stable Linear Subspace Identification: A Machine Learning Approach
by: Di Natale, Loris, et al.
Published: (2023)

A PAC-Bayes Approach for Controlling Unknown Linear Discrete-time Systems
by: Luo, Yujia, et al.
Published: (2026)

Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control
by: Skifstad, Julian, et al.
Published: (2026)

Koopman-based Deep Learning for Nonlinear System Estimation
by: Sun, Zexin, et al.
Published: (2024)

Denoising Diffusion-Based Control of Nonlinear Systems
by: Elamvazhuthi, Karthik, et al.
Published: (2024)

Iterative Learning Control of Fast, Nonlinear, Oscillatory Dynamics (Preprint)
by: Brooks, John W., et al.
Published: (2024)

How to Shrink Confidence Sets for Many Equivalent Discrete Distributions?
by: Maillard, Odalric-Ambrym, et al.
Published: (2024)

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction
by: da Silva, Samuel Filgueira, et al.
Published: (2025)

Predictive Linear Online Tracking for Unknown Targets
by: Tsiamis, Anastasios, et al.
Published: (2024)

Reinforcement Learning of Structured Control for Linear Systems with Unknown State Matrix
by: Mukherjee, Sayak, et al.
Published: (2020)