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2020 – today
- 2024
[j9]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:
A Flexible Forecasting Stack. Proc. VLDB Endow. 17(12): 3883-3892 (2024)- [i6]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:
Chronos: Learning the Language of Time Series. CoRR abs/2403.07815 (2024) - 2023
- [j8]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:
Deep Learning for Time Series Forecasting: Tutorial and Literature Survey. ACM Comput. Surv. 55(6): 121:1-121:36 (2023) - [i5]Puya Latafat, Andreas Themelis, Lorenzo Stella, Panagiotis Patrinos:
Adaptive proximal algorithms for convex optimization under local Lipschitz continuity of the gradient. CoRR abs/2301.04431 (2023) - [i4]Syama Sundar Rangapuram, Jan Gasthaus, Lorenzo Stella, Valentin Flunkert, David Salinas, Yuyang Wang, Tim Januschowski:
Deep Non-Parametric Time Series Forecaster. CoRR abs/2312.14657 (2023) - 2022
- [j7]Andreas Themelis, Lorenzo Stella, Panagiotis Patrinos:
Douglas-Rachford splitting and ADMM for nonconvex optimization: accelerated and Newton-type linesearch algorithms. Comput. Optim. Appl. 82(2): 395-440 (2022) - 2020
- [j6]Massimiliano Anselmi, Paolo Calligari, Jochen S. Hub, Marco Tartaglia, Gianfranco Bocchinfuso, Lorenzo Stella:
Structural Determinants of Phosphopeptide Binding to the N-Terminal Src Homology 2 Domain of the SHP2 Phosphatase. J. Chem. Inf. Model. 60(6): 3157-3171 (2020) - [j5]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:
GluonTS: Probabilistic and Neural Time Series Modeling in Python. J. Mach. Learn. Res. 21: 116:1-116:6 (2020) - [c7]Fadhel Ayed, Lorenzo Stella, Tim Januschowski, Jan Gasthaus:
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models. ICSOC Workshops 2020: 97-109 - [c6]Emmanuel de Bézenac, Syama Sundar Rangapuram, Konstantinos Benidis, Michael Bohlke-Schneider, Richard Kurle, Lorenzo Stella, Hilaf Hasson, Patrick Gallinari, Tim Januschowski:
Normalizing Kalman Filters for Multivariate Time Series Analysis. NeurIPS 2020 - [c5]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:
Elastic Machine Learning Algorithms in Amazon SageMaker. SIGMOD Conference 2020: 731-737 - [i3]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:
Neural forecasting: Introduction and literature overview. CoRR abs/2004.10240 (2020) - [i2]Fadhel Ayed, Lorenzo Stella, Tim Januschowski, Jan Gasthaus:
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models. CoRR abs/2007.15541 (2020)
2010 – 2019
- 2019
- [j4]Lorenzo Stella, Andreas Themelis, Panagiotis Patrinos:
Newton-Type Alternating Minimization Algorithm for Convex Optimization. IEEE Trans. Autom. Control. 64(2): 697-711 (2019) - [i1]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:
GluonTS: Probabilistic Time Series Models in Python. CoRR abs/1906.05264 (2019) - 2018
- [j3]Erica Ciotta, Paolo Prosposito, Pietro Tagliatesta, Chiara Lorecchio, Lorenzo Stella, Saulius Kaciulis, Peiman Soltani, Ernesto Placidi, Roberto Pizzoferrato:
Discriminating between Different Heavy Metal Ions with Fullerene-Derived Nanoparticles. Sensors 18(5): 1496 (2018) - [j2]Andreas Themelis, Lorenzo Stella, Panagiotis Patrinos:
Forward-Backward Envelope for the Sum of Two Nonconvex Functions: Further Properties and Nonmonotone Linesearch Algorithms. SIAM J. Optim. 28(3): 2274-2303 (2018) - [c4]Syama Sundar Rangapuram, Matthias W. Seeger, Jan Gasthaus, Lorenzo Stella, Yuyang Wang, Tim Januschowski:
Deep State Space Models for Time Series Forecasting. NeurIPS 2018: 7796-7805 - 2017
- [j1]Lorenzo Stella, Andreas Themelis, Panagiotis Patrinos:
Forward-backward quasi-Newton methods for nonsmooth optimization problems. Comput. Optim. Appl. 67(3): 443-487 (2017) - [c3]Lorenzo Stella, Andreas Themelis, Pantelis Sopasakis, Panagiotis Patrinos:
A simple and efficient algorithm for nonlinear model predictive control. CDC 2017: 1939-1944 - 2016
- [c2]Puya Latafat, Lorenzo Stella, Panagiotis Patrinos:
New primal-dual proximal algorithm for distributed optimization. CDC 2016: 1959-1964 - 2014
- [c1]Panagiotis Patrinos, Lorenzo Stella, Alberto Bemporad:
Douglas-rachford splitting: Complexity estimates and accelerated variants. CDC 2014: 4234-4239
Coauthor Index
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