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ORCIDNico Migenda
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2020 – today
- 2024
[j2]Nico Migenda
, Ralf Möller, Wolfram Schenck:
Adaptive local Principal Component Analysis improves the clustering of high-dimensional data. Pattern Recognit. 146: 110030 (2024)- [j1]Nico Migenda, Ralf Möller, Wolfram Schenck:
NGPCA: Clustering of high-dimensional and non-stationary data streams. Softw. Impacts 20: 100635 (2024) - [c7]Marvin Niederhaus, Nico Migenda, Julian Weller, Wolfram Schenck, Martin Kohlhase:
Technical Readiness of Prescriptive Analytics Platforms: A Survey. FRUCT 2024: 509-519 - 2022
- [c6]Christoph Hoppe, Nico Migenda, David Pelkmann, Daniel Hötte, Wolfram Schenck:
Collaborative System for Question Answering in German Case Law Documents. PRO-VE 2022: 303-312 - 2021
- [c5]Christoph Hoppe, David Pelkmann, Nico Migenda, Daniel Hötte, Wolfram Schenck:
Towards Intelligent Legal Advisors for Document Retrieval and Question-Answering in German Legal Documents. AIKE 2021: 29-32 - [c4]Tim Voigt, Nico Migenda, Marvin Schöne, David Pelkmann, Matthias Fricke, Wolfram Schenck, Martin Kohlhase:
Advanced Data Analytics Platform for Manufacturing Companies. ETFA 2021: 1-8 - [c3]Luca Steinmann, Nico Migenda, Tim Voigt, Martin Kohlhase, Wolfram Schenck:
Variational Autoencoder based Novelty Detection for Real-World Time Series. MSIE 2021: 1-7 - 2020
- [c2]Nico Migenda, Wolfram Schenck:
Adaptive Dimensionality Reduction for Local Principal Component Analysis. ETFA 2020: 1579-1586
2010 – 2019
- 2019
- [c1]Nico Migenda, Ralf Möller, Wolfram Schenck:
Adaptive Dimensionality Adjustment for Online "Principal Component Analysis". IDEAL (1) 2019: 76-84
Coauthor Index
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