Alexander Munteanu

According to our database, Alexander Munteanu authored at least 28 papers between 2014 and 2024.

Collaborative distances:

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

2024

Data subsampling for Poisson regression with pth-root-link.

Han Cheng Lie, Alexander Munteanu

CoRR, 2024

Turnstile ℓ_p leverage score sampling with applications.

Alexander Munteanu, Simon Omlor

CoRR, 2024

Optimal bounds for ℓ^p sensitivity sampling via ℓ² augmentation.

Alexander Munteanu, Simon Omlor

CoRR, 2024

Turnstile ℓp leverage score sampling with applications.

Alexander Munteanu, Simon Omlor

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Optimal bounds for ℓp sensitivity sampling via ℓ2 augmentation.

Alexander Munteanu, Simon Omlor

Proceedings of the Forty-first International Conference on Machine Learning, 2024

TU Dortmund - Center for Data Science & Simulation: Data Literacy Education an der TU Dortmund.

Henrike Weinert, Alexander Munteanu

Proceedings of the 54. Jahrestagung der Gesellschaft für Informatik, 2024

Scalable Learning of Item Response Theory Models.

Susanne Frick, Amer Krivosija, Alexander Munteanu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Almost Linear Constant-Factor Sketching for 𝓁₁ and Logistic Regression.

Alexander Munteanu, Simon Omlor, David P. Woodruff

CoRR, 2023

Almost Linear Constant-Factor Sketching for $\ell_1$ and Logistic Regression.

Alexander Munteanu, Simon Omlor, David P. Woodruff

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Optimal Sketching Bounds for Sparse Linear Regression.

Tung Mai, Alexander Munteanu, Cameron Musco, Anup Rao, Chris Schwiegelshohn, David P. Woodruff

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Bounding the Width of Neural Networks via Coupled Initialization A Worst Case Analysis.

Alexander Munteanu, Simon Omlor, Zhao Song, David P. Woodruff

Proceedings of the International Conference on Machine Learning, 2022

p-Generalized Probit Regression and Scalable Maximum Likelihood Estimation via Sketching and Coresets.

Alexander Munteanu, Simon Omlor, Christian Peters

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

Coresets and Sketches for Regression Problems on DataStreams and Distributed Data.

Alexander Munteanu

Proceedings of the Machine Learning under Resource Constraints - Volume 1: Fundamentals, 2022

Bayesian Analysis for Dimensionality and Complexity Reduction.

Zeyu Ding, Katja Ickstadt, Alexander Munteanu

Proceedings of the Machine Learning under Resource Constraints - Volume 3: Applications, 2022

2021

Oblivious Sketching for Logistic Regression.

Alexander Munteanu, Simon Omlor, David P. Woodruff

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

2020

Streaming statistical models via Merge & Reduce.

Leo N. Geppert, Katja Ickstadt, Alexander Munteanu, Christian Sohler

Int. J. Data Sci. Anal., 2020

2019

Random Projections and Sampling Algorithms for Clustering of High-Dimensional Polygonal Curves.

Stefan Meintrup, Alexander Munteanu, Dennis Rohde

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Framework for Bayesian Optimization in Embedded Subspaces.

Amin Nayebi, Alexander Munteanu, Matthias Poloczek

Proceedings of the 36th International Conference on Machine Learning, 2019

Probabilistic Smallest Enclosing Ball in High Dimensions via Subgradient Sampling.

Amer Krivosija, Alexander Munteanu

Proceedings of the 35th International Symposium on Computational Geometry, 2019

2018

On large-scale probabilistic and statistical data analysis

Alexander Munteanu

PhD thesis, 2018

Coresets-Methods and History: A Theoreticians Design Pattern for Approximation and Streaming Algorithms.

Alexander Munteanu, Chris Schwiegelshohn

Künstliche Intell., 2018

On Coresets for Logistic Regression.

Alexander Munteanu, Chris Schwiegelshohn, Christian Sohler, David P. Woodruff

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

Core Dependency Networks.

Alejandro Molina, Alexander Munteanu, Kristian Kersting

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Random projections for Bayesian regression.

Leo N. Geppert, Katja Ickstadt, Alexander Munteanu, Jens Quedenfeld, Christian Sohler

Stat. Comput., 2017

Coresets for Dependency Networks.

Alejandro Molina, Alexander Munteanu, Kristian Kersting

CoRR, 2017

2016

Correcting statistical models via empirical distribution functions.

Alexander Munteanu, Max Wornowizki

Comput. Stat., 2016

2014

Asymptotically exact streaming algorithms.

Marc Heinrich, Alexander Munteanu, Christian Sohler

CoRR, 2014

Smallest enclosing ball for probabilistic data.

Alexander Munteanu, Christian Sohler, Dan Feldman

Proceedings of the 30th Annual Symposium on Computational Geometry, 2014