Alexander Munteanu

Orcid: 0000-0001-6549-3270

According to our database1, Alexander Munteanu authored at least 22 papers between 2014 and 2024.

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Bibliography

2024
Scalable Learning of Item Response Theory Models.
CoRR, 2024

2023
Almost Linear Constant-Factor Sketching for 𝓁<sub>1</sub> and Logistic Regression.
CoRR, 2023

Almost Linear Constant-Factor Sketching for $\ell_1$ and Logistic Regression.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Optimal Sketching Bounds for Sparse Linear Regression.
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.
Proceedings of the International Conference on Machine Learning, 2022

p-Generalized Probit Regression and Scalable Maximum Likelihood Estimation via Sketching and Coresets.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Coresets and Sketches for Regression Problems on DataStreams and Distributed Data.
Proceedings of the Machine Learning under Resource Constraints - Volume 1: Fundamentals, 2022

Bayesian Analysis for Dimensionality and Complexity Reduction.
Proceedings of the Machine Learning under Resource Constraints - Volume 3: Applications, 2022

2021
Oblivious Sketching for Logistic Regression.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Streaming statistical models via Merge & Reduce.
Int. J. Data Sci. Anal., 2020

2019
Random Projections and Sampling Algorithms for Clustering of High-Dimensional Polygonal Curves.
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.
Proceedings of the 36th International Conference on Machine Learning, 2019

On Coresets for Logistic Regression.
Proceedings of the 49. Jahrestagung der Gesellschaft für Informatik, 50 Jahre Gesellschaft für Informatik, 2019

Probabilistic Smallest Enclosing Ball in High Dimensions via Subgradient Sampling.
Proceedings of the 35th International Symposium on Computational Geometry, 2019

2018
On large-scale probabilistic and statistical data analysis
PhD thesis, 2018

Coresets-Methods and History: A Theoreticians Design Pattern for Approximation and Streaming Algorithms.
Künstliche Intell., 2018

Core Dependency Networks.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Random projections for Bayesian regression.
Stat. Comput., 2017

Coresets for Dependency Networks.
CoRR, 2017

2016
Correcting statistical models via empirical distribution functions.
Comput. Stat., 2016

2014
Asymptotically exact streaming algorithms.
CoRR, 2014

Smallest enclosing ball for probabilistic data.
Proceedings of the 30th Annual Symposium on Computational Geometry, 2014


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