Parallel asynchronous lock-free algorithms for nonconvex big-data optimization. - Loris Cannelli; Gesualdo Scutari; Francisco Facchinei; Vyacheslav Kungurtsev (ACSSC, 2016)

Asynchronous Parallel Algorithms for Nonconvex Big-Data Optimization: Model and Convergence. - Loris Cannelli; Francisco Facchinei; Vyacheslav Kungurtsev; Gesualdo Scutari (CoRR, 2016)

Multi-Agent asynchronous nonconvex large-scale optimization. - Loris Cannelli; Francisco Facchinei; Gesualdo Scutari (CAMSAP, 2017)

Asynchronous parallel nonconvex large-scale optimization. - Loris Cannelli; Francisco Facchinei; Vyacheslav Kungurtsev; Gesualdo Scutari (ICASSP, 2017)

Essentially cyclic asynchronous nonconvex large-scale optimization. - Loris Cannelli; Francisco Facchinei; Vyacheslav Kungurtsev; Gesualdo Scutari (SPAWC, 2017)

Hedging using reinforcement learning: Contextual k-Armed Bandit versus Q-learning. - Loris Cannelli; Giuseppe Nuti; Marzio Sala; Oleg Szehr (CoRR, 2020)

Asynchronous parallel algorithms for nonconvex optimization. - Loris Cannelli; Francisco Facchinei; Vyacheslav Kungurtsev; Gesualdo Scutari (Math. Program., 2020)

Asynchronous Optimization Over Graphs: Linear Convergence Under Error Bound Conditions. - Loris Cannelli; Francisco Facchinei; Gesualdo Scutari; Vyacheslav Kungurtsev (IEEE Trans. Autom. Control., 2021)

Kernel Regression Imputation in Manifolds Via Bi-Linear Modeling: The Dynamic-MRI Case. - Konstantinos Slavakis; Gaurav N. Shetty; Loris Cannelli; Gesualdo Scutari; Ukash Nakarmi; Leslie Ying (IEEE Trans. Computational Imaging, 2022)

Cycle Aging Effect on Lithium-ion Battery Resistance: a Machine Learning Approach. - Simone Barcellona; Loris Cannelli; Silvia Colnago; Christian Laurano; Luigi Piegari (MetroXRAINE, 2023)

Split-Boost Neural Networks. - Raffaele Giuseppe Cestari; Gabriele Maroni; Loris Cannelli; Dario Piga; Simone Formentin (CoRR, 2023)

Multi-Agent Active Learning for Distributed Black-Box Optimization. - Loris Cannelli; Mengjia Zhu; Francesco Farina; Alberto Bemporad; Dario Piga (IEEE Control. Syst. Lett., 2023)

Temperature-Dependent State of Charge Estimation for Electric Vehicles Based on a Machine Learning Approach. - Simone Barcellona; Loris Cannelli; Lorenzo Codecasa; Silvia Colnago; Loredana Cristaldi; Christian Laurano; Gabriele Maroni (MetroXRAINE, 2024)

Neural Network-Enhanced Self-Organization for Efficient Resource Allocation in Distributed Edge Computing Environments. - Samira Hayat; Melanie Schranz; Loris Cannelli (ICFEC, 2025)

Gradient-based bilevel optimization for multi-penalty Ridge regression through matrix differential calculus. - Gabriele Maroni; Loris Cannelli; Dario Piga (Eur. J. Control, 2025)

Capacity estimation of Lithium-ion batteries through a Machine Learning approach. - Simone Barcellona; Lorenzo Codecasa; Silvia Colnago; Loris Cannelli; Christian Laurano; Gabriele Maroni (Math. Comput. Simul., 2026)