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2020 – today
- 2024
[i19]Jannis Becktepe, Julian Dierkes, Carolin Benjamins, Aditya Mohan, David Salinas, Raghu Rajan, Frank Hutter, Holger H. Hoos, Marius Lindauer, Theresa Eimer:
ARLBench: Flexible and Efficient Benchmarking for Hyperparameter Optimization in Reinforcement Learning. CoRR abs/2409.18827 (2024)- [i18]Andreas Mueller, Julien Siems, Harsha Nori, David Salinas, Arber Zela, Rich Caruana, Frank Hutter:
GAMformer: In-Context Learning for Generalized Additive Models. CoRR abs/2410.04560 (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) - [c14]David Salinas, Jacek Golebiowski, Aaron Klein, Matthias W. Seeger, Cédric Archambeau:
Optimizing Hyperparameters with Conformal Quantile Regression. ICML 2023: 29876-29893 - [i17]David Salinas, Jacek Golebiowski, Aaron Klein, Matthias W. Seeger, Cédric Archambeau:
Optimizing Hyperparameters with Conformal Quantile Regression. CoRR abs/2305.03623 (2023) - [i16]Sigrid Passano Hellan, Huibin Shen, François-Xavier Aubet, David Salinas, Aaron Klein:
Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimisation. CoRR abs/2306.16916 (2023) - [i15]David Salinas, Nick Erickson:
TabRepo: A Large Scale Repository of Tabular Model Evaluations and its AutoML Applications. CoRR abs/2311.02971 (2023) - [i14]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
- [c13]David Salinas, Matthias W. Seeger, Aaron Klein, Valerio Perrone, Martin Wistuba, Cédric Archambeau:
Syne Tune: A Library for Large Scale Hyperparameter Tuning and Reproducible Research. AutoML 2022: 16/1-23 - [i13]Oliver Borchert, David Salinas, Valentin Flunkert, Tim Januschowski, Stephan Günnemann:
Multi-Objective Model Selection for Time Series Forecasting. CoRR abs/2202.08485 (2022) - [i12]Tim Januschowski, Jan Gasthaus, Yuyang Wang, David Salinas, Valentin Flunkert, Michael Bohlke-Schneider, Laurent Callot:
Criteria for Classifying Forecasting Methods. CoRR abs/2212.03523 (2022) - 2021
- [i11]Giovanni Zappella, David Salinas, Cédric Archambeau:
A resource-efficient method for repeated HPO and NAS problems. CoRR abs/2103.16111 (2021) - [i10]David Salinas, Valerio Perrone, Olivier Cruchant, Cédric Archambeau:
A multi-objective perspective on jointly tuning hardware and hyperparameters. CoRR abs/2106.05680 (2021) - [i9]Robin Schmucker, Michele Donini, Muhammad Bilal Zafar, David Salinas, Cédric Archambeau:
Multi-objective Asynchronous Successive Halving. CoRR abs/2106.12639 (2021) - [i8]Riccardo Grazzi, Valentin Flunkert, David Salinas, Tim Januschowski, Matthias W. Seeger, Cédric Archambeau:
Meta-Forecasting by combining Global Deep Representations with Local Adaptation. CoRR abs/2111.03418 (2021) - 2020
- [j7]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) - [c12]David Salinas, Huibin Shen, Valerio Perrone:
A Quantile-based Approach for Hyperparameter Transfer Learning. ICML 2020: 8438-8448 - [c11]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 - [i7]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) - [i6]Stephan Rabanser, Tim Januschowski, Valentin Flunkert, David Salinas, Jan Gasthaus:
The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models. CoRR abs/2005.10111 (2020)
2010 – 2019
- 2019
- [j6]Felix Bießmann, Tammo Rukat, Philipp Schmidt, Prathik Naidu, Sebastian Schelter, Andrey Taptunov, Dustin Lange, David Salinas:
DataWig: Missing Value Imputation for Tables. J. Mach. Learn. Res. 20: 175:1-175:6 (2019) - [c10]Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski:
Probabilistic Forecasting with Spline Quantile Function RNNs. AISTATS 2019: 1901-1910 - [c9]Dominique Attali, André Lieutier, David Salinas:
When Convexity Helps Collapsing Complexes. SoCG 2019: 11:1-11:15 - [c8]David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico, Jan Gasthaus:
High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes. NeurIPS 2019: 6824-6834 - [i5]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) - [i4]David Salinas, Huibin Shen, Valerio Perrone:
A Copula approach for hyperparameter transfer learning. CoRR abs/1909.13595 (2019) - [i3]David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico, Jan Gasthaus:
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes. CoRR abs/1910.03002 (2019) - 2018
- [j5]Sebastian Schelter, Felix Bießmann, Tim Januschowski, David Salinas, Stephan Seufert, Gyuri Szarvas:
On Challenges in Machine Learning Model Management. IEEE Data Eng. Bull. 41(4): 5-15 (2018) - [c7]Felix Bießmann, David Salinas, Sebastian Schelter, Philipp Schmidt, Dustin Lange:
"Deep" Learning for Missing Value Imputationin Tables with Non-Numerical Data. CIKM 2018: 2017-2025 - 2017
- [j4]Joos-Hendrik Boese, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Dustin Lange, David Salinas, Sebastian Schelter, Matthias W. Seeger, Bernie Wang:
Probabilistic Demand Forecasting at Scale. Proc. VLDB Endow. 10(12): 1694-1705 (2017) - [i2]Valentin Flunkert, David Salinas, Jan Gasthaus:
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks. CoRR abs/1704.04110 (2017) - [i1]Matthias W. Seeger, Syama Sundar Rangapuram, Yuyang Wang, David Salinas, Jan Gasthaus, Tim Januschowski, Valentin Flunkert:
Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale. CoRR abs/1709.07638 (2017) - 2016
- [c6]Matthias W. Seeger, David Salinas, Valentin Flunkert:
Bayesian Intermittent Demand Forecasting for Large Inventories. NIPS 2016: 4646-4654 - 2015
- [j3]David Salinas, Florent Lafarge, Pierre Alliez:
Structure-Aware Mesh Decimation. Comput. Graph. Forum 34(6): 211-227 (2015) - 2013
- [j2]Dominique Attali, André Lieutier, David Salinas:
Vietoris-Rips complexes also provide topologically correct reconstructions of sampled shapes. Comput. Geom. 46(4): 448-465 (2013) - 2012
- [j1]Dominique Attali, André Lieutier, David Salinas:
Efficient Data Structure for Representing and Simplifying Simplicial complexes in High Dimensions. Int. J. Comput. Geom. Appl. 22(4): 279-304 (2012) - 2011
- [c5]Emmett Tomai, David Salinas, Rosendo Salazar:
A Rule-Based Framework for Modular Development of In-Game Interactive Dialogue Simulation. Intelligent Narrative Technologies 2011 - [c4]Dominique Attali, André Lieutier, David Salinas:
Vietoris-rips complexes also provide topologically correct reconstructions of sampled shapes. SCG 2011: 491-500 - [c3]Dominique Attali, André Lieutier, David Salinas:
Efficient data structure for representing and simplifying simplicial complexes in high dimensions. SCG 2011: 501-509 - 2010
- [c2]J. Gregorio Escalada, Helenca Duxans, David Conejero, Albert Asensio, David Salinas:
NewsClipping: An automatic multimedia news clipping application. CBMI 2010: 1-6
2000 – 2009
Coauthor Index
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