Ivano Notarnicola

About Ivano Notarnicola

Ivano Notarnicola, With an exceptional h-index of 14 and a recent h-index of 13 (since 2020), a distinguished researcher at Università degli Studi di Bologna, specializes in the field of Distributed Optimization, Control for Optimization, Systems and Control.

His recent articles reflect a diverse array of research interests and contributions to the field:

Stability-Certified On-Policy Data-Driven LQR via Recursive Learning and Policy Gradient

Semiglobal exponential stability of the discrete-time Arrow-Hurwicz-Uzawa primal-dual algorithm for constrained optimization

On-Policy Data-Driven Linear Quadratic Regulator via Combined Policy Iteration and Recursive Least Squares

Discrete-Time Distributed Optimization for Linear Uncertain Multi-Agent Systems

The gradient tracking is a distributed integral action

Triggered gradient tracking for asynchronous distributed optimization

GTAdam: Gradient tracking with adaptive momentum for distributed online optimization

Stability, linear convergence, and robustness of the Wang-Elia algorithm for distributed consensus optimization

Ivano Notarnicola Information

University

Position

Junior Assistant Professor

Citations(all)

650

Citations(since 2020)

610

Cited By

232

hIndex(all)

14

hIndex(since 2020)

13

i10Index(all)

18

i10Index(since 2020)

16

Email

University Profile Page

Google Scholar

Ivano Notarnicola Skills & Research Interests

Distributed Optimization

Control for Optimization

Systems and Control

Top articles of Ivano Notarnicola

Stability-Certified On-Policy Data-Driven LQR via Recursive Learning and Policy Gradient

arXiv preprint arXiv:2403.05367

2024/3/8

Semiglobal exponential stability of the discrete-time Arrow-Hurwicz-Uzawa primal-dual algorithm for constrained optimization

Mathematical Programming

2024/2/12

On-Policy Data-Driven Linear Quadratic Regulator via Combined Policy Iteration and Recursive Least Squares

2023/12/13

Discrete-Time Distributed Optimization for Linear Uncertain Multi-Agent Systems

2023/12/13

The gradient tracking is a distributed integral action

IEEE Transactions on Automatic Control

2023/2/23

Triggered gradient tracking for asynchronous distributed optimization

Automatica

2023/1/1

GTAdam: Gradient tracking with adaptive momentum for distributed online optimization

IEEE Transactions on Control of Network Systems

2022/12/27

Stability, linear convergence, and robustness of the Wang-Elia algorithm for distributed consensus optimization

2022/12/6

Passivity-based analysis of the ADMM algorithm for constraint-coupled optimization

Automatica

2022/12/1

Ivano Notarnicola
Ivano Notarnicola

H-Index: 9

Alessandro Falsone
Alessandro Falsone

H-Index: 11

Achievement and fragility of long-term equitability

2022/7/26

Ivano Notarnicola
Ivano Notarnicola

H-Index: 9

Distributed personalized gradient tracking with convex parametric models

IEEE Transactions on Automatic Control

2022/1/31

Ivano Notarnicola
Ivano Notarnicola

H-Index: 9

Giuseppe Notarstefano
Giuseppe Notarstefano

H-Index: 18

Learning-driven nonlinear optimal control via gaussian process regression

2021/12/14

Ivano Notarnicola
Ivano Notarnicola

H-Index: 9

Giuseppe Notarstefano
Giuseppe Notarstefano

H-Index: 18

Distributed constraint-coupled optimization via primal decomposition over random time-varying graphs

Automatica

2021/9/1

Gopronto: A feedback-based framework for nonlinear optimal control

arXiv preprint arXiv:2108.13308

2021/8/30

Ivano Notarnicola
Ivano Notarnicola

H-Index: 9

Giuseppe Notarstefano
Giuseppe Notarstefano

H-Index: 18

Distributed stochastic dual subgradient for constraint-coupled optimization

IEEE Control Systems Letters

2021/5/27

Distributed primal decomposition for large-scale MILPs

IEEE Transactions on Automatic Control

2021/2/4

Distributed online optimization via gradient tracking with adaptive momentum

arXiv preprint arXiv:2009.01745

2020/9

Distributed big-data optimization via blockwise gradient tracking

IEEE Transactions on Automatic Control

2020/7/13

Tracking-ADMM for distributed constraint-coupled optimization

Automatica

2020/7/1

Combining ADMM and tracking over networks for distributed constraint-coupled optimization

IFAC-PapersOnLine

2020/1/1

See List of Professors in Ivano Notarnicola University(Università degli Studi di Bologna)

Co-Authors

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