Konstantinos Benidis

According to our database, Konstantinos Benidis authored at least 17 papers between 2013 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

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

Middle-mile optimization for next-day delivery.

Konstantinos Benidis, Georgios S. Paschos, Martin Groß, George Iosifidis

CoRR, 2023

Solving Recurrent MIPs with Semi-supervised Graph Neural Networks.

Konstantinos Benidis, Ugo Rosolia, Syama Rangapuram, George Iosifidis, Georgios S. Paschos

CoRR, 2023

2022

Multivariate Quantile Function Forecaster.

Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Deep Explicit Duration Switching Models for Time Series.

Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Bernie Wang, Tim Januschowski

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series.

Syama Sundar Rangapuram, Lucien D. Werner, Konstantinos Benidis, Pedro Mercado, Jan Gasthaus, Tim Januschowski

Proceedings of the 38th International Conference on Machine Learning, 2021

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

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

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

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

Probabilistic Forecasting with Spline Quantile Function RNNs.

Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Sparse Portfolios for High-Dimensional Financial Index Tracking.

Konstantinos Benidis, Yiyong Feng, Daniel P. Palomar

IEEE Trans. Signal Process., 2018

Optimization Methods for Financial Index Tracking: From Theory to Practice.

Konstantinos Benidis, Yiyong Feng, Daniel P. Palomar

Found. Trends Optim., 2018

2016

Orthogonal Sparse PCA and Covariance Estimation via Procrustes Reformulation.

Konstantinos Benidis, Ying Sun, Prabhu Babu, Daniel P. Palomar

IEEE Trans. Signal Process., 2016

Orthogonal sparse eigenvectors: A procrustes problem.

Konstantinos Benidis, Ying Sun, Prabhu Babu, Daniel Pérez Palomar

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2013

Bidirectional relay communication with additional private message.

Konstantinos Benidis, Rafael F. Schaefer, Holger Boche

Proceedings of the 14th IEEE Workshop on Signal Processing Advances in Wireless Communications, 2013