Lorenzo Stella

According to our database, Lorenzo Stella authored at least 21 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Flexible Forecasting Stack.

Tim Januschowski, Yuyang Wang, Jan Gasthaus, Syama Sundar Rangapuram, Caner Turkmen, Jasper Zschiegner, Lorenzo Stella, Michael Bohlke-Schneider, Danielle C. Maddix, Konstantinos Benidis, Alexander Alexandrov, Christos Faloutsos, Sebastian Schelter

Proc. VLDB Endow., August, 2024

Chronos: Learning the Language of Time Series.

Abdul Fatir Ansari, Lorenzo Stella, Ali Caner Türkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda-Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Yuyang Wang

CoRR, 2024

2023

Deep Learning for Time Series Forecasting: Tutorial and Literature Survey.

Konstantinos Benidis, Syama Sundar Rangapuram, Valentin Flunkert, Yuyang Wang, Danielle C. Maddix, Ali Caner Türkmen, Jan Gasthaus, Michael Bohlke-Schneider, David Salinas, Lorenzo Stella, François-Xavier Aubet, Laurent Callot, Tim Januschowski

ACM Comput. Surv., 2023

Deep Non-Parametric Time Series Forecaster.

Syama Sundar Rangapuram, Jan Gasthaus, Lorenzo Stella, Valentin Flunkert, David Salinas, Yuyang Wang, Tim Januschowski

CoRR, 2023

Adaptive proximal algorithms for convex optimization under local Lipschitz continuity of the gradient.

Puya Latafat, Andreas Themelis, Lorenzo Stella, Panagiotis Patrinos

CoRR, 2023

2022

Douglas-Rachford splitting and ADMM for nonconvex optimization: accelerated and Newton-type linesearch algorithms.

Andreas Themelis, Lorenzo Stella, Panagiotis Patrinos

Comput. Optim. Appl., 2022

2020

GluonTS: Probabilistic and Neural Time Series Modeling in Python.

Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Sundar Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang

J. Mach. Learn. Res., 2020

Structural Determinants of Phosphopeptide Binding to the N-Terminal Src Homology 2 Domain of the SHP2 Phosphatase.

Massimiliano Anselmi, Paolo Calligari, Jochen S. Hub, Marco Tartaglia, Gianfranco Bocchinfuso, Lorenzo Stella

J. Chem. Inf. Model., 2020

Neural forecasting: Introduction and literature overview.

Konstantinos Benidis, Syama Sundar Rangapuram, Valentin Flunkert, Bernie Wang, Danielle C. Maddix, Ali Caner Türkmen, Jan Gasthaus, Michael Bohlke-Schneider, David Salinas, Lorenzo Stella, Laurent Callot, Tim Januschowski

CoRR, 2020

Elastic Machine Learning Algorithms in Amazon SageMaker.

Edo Liberty, Zohar S. Karnin, Bing Xiang, Laurence Rouesnel, Baris Coskun, Ramesh Nallapati, Julio Delgado, Amir Sadoughi, Yury Astashonok, Piali Das, Can Balioglu, Saswata Chakravarty, Madhav Jha, Philip Gautier, David Arpin, Tim Januschowski, Valentin Flunkert, Yuyang Wang, Jan Gasthaus, Lorenzo Stella, Syama Sundar Rangapuram, David Salinas, Sebastian Schelter, Alex Smola

Proceedings of the 2020 International Conference on Management of Data, 2020

Normalizing Kalman Filters for Multivariate Time Series Analysis.

Emmanuel de Bézenac, Syama Sundar Rangapuram, Konstantinos Benidis, Michael Bohlke-Schneider, Richard Kurle, Lorenzo Stella, Hilaf Hasson, Patrick Gallinari, Tim Januschowski

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models.

Fadhel Ayed, Lorenzo Stella, Tim Januschowski, Jan Gasthaus

Proceedings of the Service-Oriented Computing - ICSOC 2020 Workshops, 2020

2019

Newton-Type Alternating Minimization Algorithm for Convex Optimization.

Lorenzo Stella, Andreas Themelis, Panagiotis Patrinos

IEEE Trans. Autom. Control., 2019

GluonTS: Probabilistic Time Series Models in Python.

Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Sundar Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang

CoRR, 2019

2018

Forward-Backward Envelope for the Sum of Two Nonconvex Functions: Further Properties and Nonmonotone Linesearch Algorithms.

Andreas Themelis, Lorenzo Stella, Panagiotis Patrinos

SIAM J. Optim., 2018

Discriminating between Different Heavy Metal Ions with Fullerene-Derived Nanoparticles.

Erica Ciotta, Paolo Prosposito, Pietro Tagliatesta, Chiara Lorecchio, Lorenzo Stella, Saulius Kaciulis, Peiman Soltani, Ernesto Placidi, Roberto Pizzoferrato

Sensors, 2018

Deep State Space Models for Time Series Forecasting.

Syama Sundar Rangapuram, Matthias W. Seeger, Jan Gasthaus, Lorenzo Stella, Yuyang Wang, Tim Januschowski

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Forward-backward quasi-Newton methods for nonsmooth optimization problems.

Lorenzo Stella, Andreas Themelis, Panagiotis Patrinos

Comput. Optim. Appl., 2017

A simple and efficient algorithm for nonlinear model predictive control.

Lorenzo Stella, Andreas Themelis, Pantelis Sopasakis, Panagiotis Patrinos

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

2016

New primal-dual proximal algorithm for distributed optimization.

Puya Latafat, Lorenzo Stella, Panagiotis Patrinos

Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2014

Douglas-rachford splitting: Complexity estimates and accelerated variants.

Panagiotis Patrinos, Lorenzo Stella, Alberto Bemporad

Proceedings of the 53rd IEEE Conference on Decision and Control, 2014