Adrian Englhardt

Publication Activity (10 Years)

Years Active: 2015-2022
Publications (10 Years): 12

Top Topics

Active Learning

Event Detection

Top Venues

Int. J. Digit. Libr.

Publications

Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm
Efficient SVDD sampling with approximation guarantees for the decision boundary. Mach. Learn. 111 (4) (2022)
Holger Trittenbach, Adrian Englhardt, Klemens Böhm
An overview and a benchmark of active learning for outlier detection with one-class classifiers. Expert Syst. Appl. 168 (2021)
Adrian Englhardt, Holger Trittenbach, Dennis Vetter, Klemens Böhm
Finding the Sweet Spot: Batch Selection for One-Class Active Learning. SDM (2020)
Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm
Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary. CoRR (2020)
Adrian Englhardt, Klemens Böhm
Exploring the Unknown - Query Synthesis in One-Class Active Learning. SDM (2020)
Ábel Elekes, Adrian Englhardt, Martin Schäler, Klemens Böhm
Toward meaningful notions of similarity in NLP embedding models. Int. J. Digit. Libr. 21 (2) (2020)
Adrian Englhardt, Jens Willkomm, Martin Schäler, Klemens Böhm
Improving semantic change analysis by combining word embeddings and word frequencies. Int. J. Digit. Libr. 21 (3) (2020)
Michael Vollmer, Adrian Englhardt, Holger Trittenbach, Pawel Bielski, Shahab Karrari, Klemens Böhm
Energy Time-Series Features for Emerging Applications on the Basis of Human-Readable Machine Descriptions. e-Energy (2019)
Holger Trittenbach, Adrian Englhardt, Klemens Böhm
An Overview and a Benchmark of Active Learning for One-Class Classification. CoRR (2018)
Ábel Elekes, Adrian Englhardt, Martin Schäler, Klemens Böhm
Resources to Examine the Quality of Word Embedding Models Trained on n-Gram Data. CoNLL (2018)
Gregor Hollmig, Matthias Horne, Simon Leimkühler, Frederik Schöll, Carsten Strunk, Adrian Englhardt, Pavel Efros, Erik Buchmann, Klemens Böhm
An evaluation of combinations of lossy compression and change-detection approaches for time-series data. Inf. Syst. 65 (2017)
Pavel Efros, Erik Buchmann, Adrian Englhardt, Klemens Böhm
How to Quantify the Impact of Lossy Transformations on Event Detection. Big Data Res. 9 (2017)
Pavel Efros, Erik Buchmann, Adrian Englhardt, Klemens Böhm
How to quantify the impact of lossy transformations on change detection. SSDBM (2015)