:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Veedu, Mishfad Shaikh, Deka, Deepjyoti, Salapaka, Murti V.
Formato:	Preprint
Publicado:	2023
Materias:	Machine Learning Systems and Control Optimization and Control
Acceso en línea:	https://arxiv.org/abs/2308.16859
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Topology Learning of unknown Networked Linear Dynamical System excited by Cyclostationary inputs
por: Doddi, Harish, et al.
Publicado: (2020)

Uncovering the Influence Flow Model of Transistor Amplifiers, Its Reconstruction and Application
por: Rana, Mohammed Tuhin, et al.
Publicado: (2025)

Distributed Difference of Convex Optimization
por: Khatana, Vivek, et al.
Publicado: (2024)

Function Gradient Approximation with Random Shallow ReLU Networks with Control Applications
por: Lamperski, Andrew, et al.
Publicado: (2024)

Watts vs. Bytes: Turning Data Centers into Grid Assets via Storage Compute Co-Optimization
por: Liu, Shaohui, et al.
Publicado: (2026)

PPGN: Physics-Preserved Graph Networks for Real-Time Fault Location in Distribution Systems with Limited Observation and Labels
por: Li, Wenting, et al.
Publicado: (2021)

Mitigating the Impact of Uncertain Wildfire Risk on Power Grids through Topology Control
por: Zhou, Yuqi, et al.
Publicado: (2023)

The value of storage in electricity distribution: The role of markets
por: Lauinger, Dirk, et al.
Publicado: (2025)

Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens
por: Moghaddam, Amirreza Neshaei, et al.
Publicado: (2024)

The Sample Complexity of Online Reinforcement Learning: A Multi-model Perspective
por: Muehlebach, Michael, et al.
Publicado: (2025)

Learning Power Flow with Confidence: A Probabilistic Guarantee Framework for Voltage Risk
por: Pareek, Parikshit, et al.
Publicado: (2023)

Variance-Reduced Cascade Q-learning: Algorithms and Sample Complexity
por: Boveiri, Mohammad, et al.
Publicado: (2024)

Sample Complexity of Linear Quadratic Regulator Without Initial Stability
por: Moghaddam, Amirreza Neshaei, et al.
Publicado: (2025)

Learning Optimal Control and Dynamical Structure of Global Trajectory Search Problems with Diffusion Models
por: Graebner, Jannik, et al.
Publicado: (2024)

Estimation Sample Complexity of a Class of Nonlinear Continuous-time Systems
por: Kuang, Simon, et al.
Publicado: (2023)

Identification and Adaptive Control of Markov Jump Systems: Sample Complexity and Regret Bounds
por: Sattar, Yahya, et al.
Publicado: (2021)

Safe and Near-Optimal Control with Online Dynamics Learning
por: Prajapat, Manish, et al.
Publicado: (2025)

A Control Theoretic Framework for Adaptive Gradient Optimizers in Machine Learning
por: Chakrabarti, Kushal, et al.
Publicado: (2022)

Finite Sample Identification of Partially Observed Bilinear Dynamical Systems
por: Sattar, Yahya, et al.
Publicado: (2025)

Mutual Information Optimal Control of Discrete-Time Linear Systems
por: Enami, Shoju, et al.
Publicado: (2025)

On Policy Stochasticity in Mutual Information Optimal Control of Linear Systems
por: Enami, Shoju, et al.
Publicado: (2025)

Action Dependency Graphs for Globally Optimal Coordinated Reinforcement Learning
por: Ding, Jianglin, et al.
Publicado: (2025)

Finite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics
por: Prajapat, Manish, et al.
Publicado: (2025)

Data-Efficient Strategies for Probabilistic Voltage Envelopes under Network Contingencies
por: Pareek, Parikshit, et al.
Publicado: (2023)

Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates
por: Maity, Sreejeet, et al.
Publicado: (2025)

Physics-Informed Graph Neural Network for Dynamic Reconfiguration of Power Systems
por: Authier, Jules, et al.
Publicado: (2023)

End-to-End Learning Framework for Solving Non-Markovian Optimal Control
por: Zhang, Xiaole, et al.
Publicado: (2025)

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

Mutual Information Optimal Density Control of Linear Systems and Generalized Schrödinger Bridges with Reference Refinement
por: Enami, Shoju, et al.
Publicado: (2026)

Towards Enabling Learning for Time-Varying finite horizon Sequential Decision-Making Problems*
por: Tiwari, Dhananjay, et al.
Publicado: (2025)

Learning-Based Optimal Control with Performance Guarantees for Unknown Systems with Latent States
por: Lefringhausen, Robert, et al.
Publicado: (2023)

Learning Exactly Linearizable Deep Dynamics Models
por: Moriyasu, Ryuta, et al.
Publicado: (2023)

Learning Linear Dynamics from Bilinear Observations
por: Sattar, Yahya, et al.
Publicado: (2024)

Safely Learning Dynamical Systems
por: Ahmadi, Amir Ali, et al.
Publicado: (2023)

Learning Dissipative Neural Dynamical Systems
por: Xu, Yuezhu, et al.
Publicado: (2023)

Finite Sample Frequency Domain Identification
por: Tsiamis, Anastasios, et al.
Publicado: (2024)

The Ground Cost for Optimal Transport of Angular Velocity
por: Elamvazhuthi, Karthik, et al.
Publicado: (2025)

Learning of Linear Dynamical Systems as a Non-Commutative Polynomial Optimization Problem
por: Zhou, Quan, et al.
Publicado: (2020)

Deterministic Trajectory Optimization through Probabilistic Optimal Control
por: Filabadi, Mohammad Mahmoudi, et al.
Publicado: (2024)

Towards an Optimal Control Perspective of ResNet Training
por: Püttschneider, Jens, et al.
Publicado: (2025)