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ORCIDVadim Arzamasov
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2020 – today
- 2024
[j2]Marco Heyden
, Edouard Fouché, Vadim Arzamasov, Tanja Fenn, Florian Kalinke, Klemens Böhm:
Adaptive Bernstein change detector for high-dimensional data streams. Data Min. Knowl. Discov. 38(3): 1334-1363 (2024)- [j1]Jose Cribeiro-Ramallo, Vadim Arzamasov, Klemens Böhm:
Efficient Generation of Hidden Outliers for Improved Outlier Detection. ACM Trans. Knowl. Discov. Data 18(9): 234:1-234:21 (2024) - [c8]Vadim Arzamasov, Klemens Böhm:
A Reproducibility Study of Subgroup Discovery Algorithms. ADBIS (Short Papers) 2024: 3-13 - [c7]Marco Heyden, Vadim Arzamasov, Edouard Fouché, Klemens Böhm:
Budgeted Multi-Armed Bandits with Asymmetric Confidence Intervals. KDD 2024: 1073-1084 - [i9]Jose Cribeiro-Ramallo, Vadim Arzamasov, Klemens Böhm:
Efficient Generation of Hidden Outliers for Improved Outlier Detection. CoRR abs/2402.03846 (2024) - [i8]Jose Cribeiro-Ramallo, Vadim Arzamasov, Federico Matteucci, Denis Wambold, Klemens Böhm:
Generative Subspace Adversarial Active Learning for Outlier Detection in Multiple Views of High-dimensional Data. CoRR abs/2404.14451 (2024) - [i7]Federico Matteucci, Vadim Arzamasov, Jose Cribeiro-Ramallo, Marco Heyden, Konstantin Ntounas, Klemens Böhm:
Generalizability of experimental studies. CoRR abs/2406.17374 (2024) - [i6]Vadim Arzamasov, Klemens Böhm:
Evaluating Privacy Measures for Load Hiding. CoRR abs/2408.06460 (2024) - 2023
- [c6]Federico Matteucci, Vadim Arzamasov, Klemens Böhm:
A benchmark of categorical encoders for binary classification. NeurIPS 2023 - [i5]Marco Heyden, Vadim Arzamasov, Edouard Fouché, Klemens Böhm:
Budgeted Multi-Armed Bandits with Asymmetric Confidence Intervals. CoRR abs/2306.07071 (2023) - [i4]Marco Heyden, Edouard Fouché, Vadim Arzamasov, Tanja Fenn, Florian Kalinke, Klemens Böhm:
Adaptive Bernstein Change Detector for High-Dimensional Data Streams. CoRR abs/2306.12974 (2023) - [i3]Federico Matteucci, Vadim Arzamasov, Klemens Böhm:
A benchmark of categorical encoders for binary classification. CoRR abs/2307.09191 (2023) - 2021
- [b1]Vadim Arzamasov:
Comprehensible and Robust Knowledge Discovery from Small Datasets. Karlsruhe Institute of Technology, Germany, 2021 - [c5]Vadim Arzamasov, Klemens Böhm:
REDS: Rule Extraction for Discovering Scenarios. SIGMOD Conference 2021: 115-128 - [i2]Vadim Arzamasov, Benjamin Jochum, Klemens Böhm:
Pedagogical Rule Extraction for Learning Interpretable Models. CoRR abs/2112.13285 (2021) - 2020
- [c4]Vadim Arzamasov, Rebecca Schwerdt, Shahab Karrari, Klemens Böhm, Tien Bach Nguyen:
Privacy Measures and Storage Technologies for Battery-Based Load Hiding - an Overview and Experimental Study. e-Energy 2020: 178-195
2010 – 2019
- 2019
- [c3]Vadim Arzamasov, Klemens Böhm, Ignaz Rutter:
Minimizing Bias in Estimation of Mutual Information from Data Streams. SSDBM 2019: 1-12 - [i1]Vadim Arzamasov, Klemens Böhm:
Scenario Discovery via Rule Extraction. CoRR abs/1910.01713 (2019) - 2018
- [c2]Vadim Arzamasov, Klemens Böhm, Patrick Jochem:
Towards Concise Models of Grid Stability. SmartGridComm 2018: 1-6 - [d1]Vadim Arzamasov:
Electrical Grid Stability Simulated Data. UCI Machine Learning Repository, 2018
- 2014
- [c1]Vadim Arzamasov, Henry Penikas:
A Financial Stability Index for Israel. ITQM 2014: 985-994
Coauthor Index
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