Linara Adilova

According to our database, Linara Adilova authored at least 18 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Layerwise Linear Mode Connectivity.

Linara Adilova, Asja Fischer, Martin Jaggi

CoRR, 2023

Guideline for Trustworthy Artificial Intelligence - AI Assessment Catalog.

Maximilian Poretschkin, Anna Schmitz, Maram Akila, Linara Adilova, Daniel Becker, Armin B. Cremers, Dirk Hecker, Sebastian Houben, Michael Mock, Julia Rosenzweig, Joachim Sicking, Elena Schulz, Angelika Voss, Stefan Wrobel

CoRR, 2023

FAM: Relative Flatness Aware Minimization.

Linara Adilova, Amr Abourayya, Jianning Li, Amin Dada, Henning Petzka, Jan Egger, Jens Kleesiek, Michael Kamp

Proceedings of the Topological, 2023

Information Plane Analysis for Dropout Neural Networks.

Linara Adilova, Bernhard C. Geiger, Asja Fischer

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Visual Analytics for Human-Centered Machine Learning.

Natalia V. Andrienko, Gennady L. Andrienko, Linara Adilova, Stefan Wrobel, Theresa-Marie Rhyne

IEEE Computer Graphics and Applications, 2022

2021

Novelty Detection in Sequential Data by Informed Clustering and Modeling.

Linara Adilova, Siming Chen, Michael Kamp

CoRR, 2021

Approaches to Uncertainty Quantification in Federated Deep Learning.

Florian Linsner, Linara Adilova, Sina Däubener, Michael Kamp, Asja Fischer

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

Relative Flatness and Generalization.

Henning Petzka, Michael Kamp, Linara Adilova, Cristian Sminchisescu, Mario Boley

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation.

Linara Adilova, Elena Schulz, Maram Akila, Sebastian Houben, Jan David Schneider, Fabian Hüger, Tim Wirtz

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020

LDA Ensembles for Interactive Exploration and Categorization of Behaviors.

Siming Chen, Natalia V. Andrienko, Gennady L. Andrienko, Linara Adilova, Jérémie Barlet, Jörg Kindermann, Phong H. Nguyen, Olivier Thonnard, Cagatay Turkay

IEEE Trans. Vis. Comput. Graph., 2020

Feature-Robustness, Flatness and Generalization Error for Deep Neural Networks.

Henning Petzka, Linara Adilova, Michael Kamp, Cristian Sminchisescu

CoRR, 2020

Resource-Constrained On-Device Learning by Dynamic Averaging.

Lukas Heppe, Michael Kamp, Linara Adilova, Danny Heinrich, Nico Piatkowski, Katharina Morik

Proceedings of the ECML PKDD 2020 Workshops, 2020

2019

A Reparameterization-Invariant Flatness Measure for Deep Neural Networks.

Henning Petzka, Linara Adilova, Michael Kamp, Cristian Sminchisescu

CoRR, 2019

Information-Theoretic Perspective of Federated Learning.

Linara Adilova, Julia Rosenzweig, Michael Kamp

CoRR, 2019

System Misuse Detection Via Informed Behavior Clustering and Modeling.

Linara Adilova, Livin Natious, Siming Chen, Olivier Thonnard, Michael Kamp

Proceedings of the 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2019

2018

Making Efficient Use of a Domain Expert's Time in Relation Extraction.

Linara Adilova, Sven Giesselbach, Stefan Rüping

CoRR, 2018

Efficient Decentralized Deep Learning by Dynamic Model Averaging.

Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Introducing Noise in Decentralized Training of Neural Networks.

Linara Adilova, Nathalie Paul, Peter Schlicht

Proceedings of the ECML PKDD 2018 Workshops, 2018