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Kai Labusch
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2020 – today
- 2023
- [c16]Kai Labusch
, Clemens Neudecker
Gauging the Limitations of Natural Language Supervised Text-Image Metrics Learning by Iconclass Visual Concepts. HIP@ICDAR 2023: 19-24 - [c15]Vahid Rezanezhad
Document Layout Analysis with Deep Learning and Heuristics. HIP@ICDAR 2023: 73-78 - 2022
- [c14]Kai Labusch, Clemens Neudecker:
Entity Linking in Multilingual Newspapers and Classical Commentaries with BERT. CLEF (Working Notes) 2022: 1079-1089 - 2020
- [c13]Kai Labusch, Clemens Neudecker:
Named Entity Disambiguation and Linking Historic Newspaper OCR with BERT. CLEF (Working Notes) 2020 - [c12]Georg Rehm, Peter Bourgonje, Stefanie Hegele, Florian Kintzel, Julián Moreno Schneider, Malte Ostendorff, Karolina Zaczynska, Armin Berger, Stefan Grill, Sören Räuchle, Jens Rauenbusch, Lisa Rutenburg, André Schmidt, Mikka Wild, Henry Hoffmann, Julian Fink, Sarah Schulz, Jurica Seva, Joachim Quantz, Joachim Böttger, Josefine Matthey, Rolf Fricke, Jan Thomsen, Adrian Paschke, Jamal Al Qundus, Thomas Hoppe, Naouel Karam, Frauke Weichhardt, Christian Fillies, Clemens Neudecker, Mike Gerber, Kai Labusch, Vahid Rezanezhad, Robin Schaefer, David Zellhöfer, Daniel Siewert, Patrick Bunk, Lydia Pintscher, Elena Aleynikova, Franziska Heine:
QURATOR: Innovative Technologies for Content and Data Curation. Qurator 2020 - [i1]Georg Rehm, Peter Bourgonje, Stefanie Hegele, Florian Kintzel, Julián Moreno Schneider, Malte Ostendorff, Karolina Zaczynska, Armin Berger, Stefan Grill, Sören Räuchle, Jens Rauenbusch, Lisa Rutenburg, André Schmidt, Mikka Wild, Henry Hoffmann, Julian Fink, Sarah Schulz, Jurica Seva, Joachim Quantz, Joachim Böttger, Josefine Matthey, Rolf Fricke, Jan Thomsen, Adrian Paschke, Jamal Al Qundus, Thomas Hoppe, Naouel Karam, Frauke Weichhardt, Christian Fillies, Clemens Neudecker
QURATOR: Innovative Technologies for Content and Data Curation. CoRR abs/2004.12195 (2020)
2010 – 2019
- 2019
- [c11]Kai Labusch, Clemens Neudecker, David Zellhöfer:
BERT for Named Entity Recognition in Contemporary and Historic German. KONVENS 2019 - 2012
- [b1]Kai Labusch:
Soft-competitive learning of sparse data models. University of Lübeck, 2012 - [j6]Jens Hocke, Kai Labusch, Erhardt Barth, Thomas Martinetz:
Sparse Coding and Selected Applications. Künstliche Intell. 26(4): 349-355 (2012) - 2011
- [j5]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Soft-competitive learning of sparse codes and its application to image reconstruction. Neurocomputing 74(9): 1418-1428 (2011) - [j4]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Robust and Fast Learning of Sparse Codes With Stochastic Gradient Descent. IEEE J. Sel. Top. Signal Process. 5(5): 1048-1060 (2011) - 2010
- [c10]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Bag of Pursuits and Neural Gas for Improved Sparse Coding. COMPSTAT 2010: 327-336 - [c9]Kai Labusch, Thomas Martinetz:
Learning sparse codes for image reconstruction. ESANN 2010 - [c8]Ingrid Brænne, Kai Labusch, Amir Madany Mamlouk:
Sparse Coding for Feature Selection on Genome-Wide Association Data. ICANN (1) 2010: 337-346
2000 – 2009
- 2009
- [j3]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Sparse Coding Neural Gas: Learning of overcomplete data representations. Neurocomputing 72(7-9): 1547-1555 (2009) - [j2]Thomas Martinetz, Kai Labusch, Daniel Schneegaß:
SoftDoubleMaxMinOver: Perceptron-Like Training of Support Vector Machines. IEEE Trans. Neural Networks 20(7): 1061-1072 (2009) - [c7]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Approaching the Time Dependent Cocktail Party Problem with Online Sparse Coding Neural Gas. WSOM 2009: 145-153 - 2008
- [j1]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Simple Method for High-Performance Digit Recognition Based on Sparse Coding. IEEE Trans. Neural Networks 19(11): 1985-1989 (2008) - [c6]Kai Labusch, Fabian Timm, Thomas Martinetz:
Simple Incremental One-Class Support Vector Classification. DAGM-Symposium 2008: 21-30 - [c5]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Learning Data Representations with Sparse Coding Neural Gas. ESANN 2008: 233-238 - [c4]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Sparse Coding Neural Gas for the Separation of Noisy Overcomplete Sources. ICANN (1) 2008: 788-797 - 2007
- [c3]Kai Labusch, Udo Siewert, Thomas Martinetz, Erhardt Barth:
Learning optimal features for visual pattern recognition. Human Vision and Electronic Imaging 2007: 64920B - 2006
- [c2]Daniel Schneegaß, Kai Labusch, Thomas Martinetz:
MaxMinOver Regression: A Simple Incremental Approach for Support Vector Function Approximation. ICANN (1) 2006: 150-158 - 2005
- [c1]Thomas Martinetz, Kai Labusch, Daniel Schneegaß:
SoftDoubleMinOver: A Simple Procedure for Maximum Margin Classification. ICANN (2) 2005: 301-306
Coauthor Index
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