Flexible selective parallel algorithms for big data optimization. - Amir Daneshmand; Francisco Facchinei; Vyacheslav Kungurtsev; Gesualdo Scutari (ACSSC, 2014)

Hybrid Random/Deterministic Parallel Algorithms for Nonconvex Big Data Optimization. - Amir Daneshmand; Francisco Facchinei; Vyacheslav Kungurtsev; Gesualdo Scutari (CoRR, 2014)

Hybrid Random/Deterministic Parallel Algorithms for Convex and Nonconvex Big Data Optimization. - Amir Daneshmand; Francisco Facchinei; Vyacheslav Kungurtsev; Gesualdo Scutari (IEEE Trans. Signal Process., 2015)

Distributed dictionary learning. - Amir Daneshmand; Gesualdo Scutari; Francisco Facchinei (ACSSC, 2016)

D2L: Decentralized dictionary learning over dynamic networks. - Amir Daneshmand; Ying Sun 003; Gesualdo Scutari; Francisco Facchinei (ICASSP, 2017)

Second-order Guarantees of Gradient Algorithms over Networks. - Amir Daneshmand; Gesualdo Scutari; Vyacheslav Kungurtsev (Allerton, 2018)

Convergence Rate of Distributed Optimization Algorithms Based on Gradient Tracking. - Ying Sun 003; Amir Daneshmand; Gesualdo Scutari (CoRR, 2019)

Decentralized Dictionary Learning Over Time-Varying Digraphs. - Amir Daneshmand; Ying Sun 003; Gesualdo Scutari; Francisco Facchinei; Brian M. Sadler (J. Mach. Learn. Res., 2019)

Second-Order Guarantees of Distributed Gradient Algorithms. - Amir Daneshmand; Gesualdo Scutari; Vyacheslav Kungurtsev (SIAM J. Optim., 2020)

An Accelerated Second-Order Method for Distributed Stochastic Optimization. - Artem Agafonov; Pavel E. Dvurechensky; Gesualdo Scutari; Alexander V. Gasnikov; Dmitry Kamzolov; Aleksandr Lukashevich; Amir Daneshmand (CDC, 2021)

Newton Method over Networks is Fast up to the Statistical Precision. - Amir Daneshmand; Gesualdo Scutari; Pavel E. Dvurechensky; Alexander V. Gasnikov (ICML, 2021)

Distributed Optimization Based on Gradient Tracking Revisited: Enhancing Convergence Rate via Surrogation. - Ying Sun 003; Gesualdo Scutari; Amir Daneshmand (SIAM J. Optim., 2022)