Linara Adilova

36 papers A* 3Journal 22Unranked 7
YearRankTypeTitle / Venue / Authors
2025 J jnl
Fisher information flow in artificial neural networks.
CoRR
Maximilian Weimar, Lukas M. Rachbauer, Ilya Starshynov, Daniele Faccio, Linara Adilova, Dorian Bouchet, Stefan Rotter
2025 J jnl
Flatness is Necessary, Neural Collapse is Not: Rethinking Generalization via Grokking.
CoRR
Ting Han, Linara Adilova, Henning Petzka, Jens Kleesiek, Michael Kamp
2025 — —
Generalization in deep learning: from theory to practice.
Linara Adilova
2025 J jnl
Re-interpreting rules interpretability.
Int. J. Data Sci. Anal.
Linara Adilova, Michael Kamp, Gennady L. Andrienko, Natalia V. Andrienko
2025 J jnl
When Flatness Does (Not) Guarantee Adversarial Robustness.
CoRR
Nils Philipp Walter, Linara Adilova, Jilles Vreeken, Michael Kamp
2024 J jnl
Landscaping Linear Mode Connectivity.
CoRR
Sidak Pal Singh, Linara Adilova, Michael Kamp, Asja Fischer, Bernhard Schölkopf, Thomas Hofmann
2024 A* conf
Layer-wise linear mode connectivity.
ICLR
Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi
2024 J jnl
The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective.
CoRR
Nils Philipp Walter, Linara Adilova, Jilles Vreeken, Michael Kamp
2023 — conf
FAM: Relative Flatness Aware Minimization.
TAG-ML
Linara Adilova, Amr Abourayya, Jianning Li, Amin Dada, Henning Petzka, Jan Egger, Jens Kleesiek, Michael Kamp
2023 J jnl
FAM: Relative Flatness Aware Minimization.
CoRR
Linara Adilova, Amr Abourayya, Jianning Li, Amin Dada, Henning Petzka, Jan Egger, Jens Kleesiek, Michael Kamp
2023 J jnl
Guideline for Trustworthy Artificial Intelligence - AI Assessment Catalog.
CoRR
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
2023 A* conf
Information Plane Analysis for Dropout Neural Networks.
ICLR
Linara Adilova, Bernhard C. Geiger, Asja Fischer
2023 J jnl
Information Plane Analysis for Dropout Neural Networks.
CoRR
Linara Adilova, Bernhard C. Geiger, Asja Fischer
2023 J jnl
Layerwise Linear Mode Connectivity.
CoRR
Linara Adilova, Asja Fischer, Martin Jaggi
2022 J jnl
Visual Analytics for Human-Centered Machine Learning.
IEEE Computer Graphics and Applications
Natalia V. Andrienko, Gennady L. Andrienko, Linara Adilova, Stefan Wrobel, Theresa-Marie Rhyne
2021 — conf
Approaches to Uncertainty Quantification in Federated Deep Learning.
PKDD/ECML Workshops (1)
Florian Linsner, Linara Adilova, Sina Däubener, Michael Kamp, Asja Fischer
2021 — ed.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I
PKDD/ECML Workshops (1)
Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça
2021 — ed.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II
PKDD/ECML Workshops (2)
Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça
2021 J jnl
Novelty Detection in Sequential Data by Informed Clustering and Modeling.
CoRR
Linara Adilova, Siming Chen, Michael Kamp
2021 — conf
Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation.
CVPR Workshops
Linara Adilova, Elena Schulz, Maram Akila, Sebastian Houben, Jan David Schneider, Fabian Hüger, Tim Wirtz
2021 J jnl
Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation.
CoRR
Linara Adilova, Elena Schulz, Maram Akila, Sebastian Houben, Jan David Schneider, Fabian Hüger, Tim Wirtz
2021 A* conf
Relative Flatness and Generalization.
NeurIPS
Henning Petzka, Michael Kamp, Linara Adilova, Cristian Sminchisescu, Mario Boley
2020 — ed.
ECML PKDD 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14-18, 2020, Proceedings
PKDD/ECML Workshops
Irena Koprinska, Michael Kamp, Annalisa Appice, Corrado Loglisci, Luiza Antonie, Albrecht Zimmermann, Riccardo Guidotti, Özlem Özgöbek, Rita P. Ribeiro, Ricard Gavaldà, João Gama, Linara Adilova, Yamuna Krishnamurthy, Pedro M. Ferreira, Donato Malerba, Ibéria Medeiros, Michelangelo Ceci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras, Peter Christen, Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Anna Monreale, Przemyslaw Biecek, Salvatore Rinzivillo, Benjamin Kille, Andreas Lommatzsch, Jon Atle Gulla
2020 J jnl
Feature-Robustness, Flatness and Generalization Error for Deep Neural Networks.
CoRR
Henning Petzka, Linara Adilova, Michael Kamp, Cristian Sminchisescu
2020 J jnl
LDA Ensembles for Interactive Exploration and Categorization of Behaviors.
IEEE Trans. Vis. Comput. Graph.
Siming Chen, Natalia V. Andrienko, Gennady L. Andrienko, Linara Adilova, Jérémie Barlet, Jörg Kindermann, Phong H. Nguyen, Olivier Thonnard, Cagatay Turkay
2020 — conf
Resource-Constrained On-Device Learning by Dynamic Averaging.
PKDD/ECML Workshops
Lukas Heppe, Michael Kamp, Linara Adilova, Danny Heinrich, Nico Piatkowski, Katharina Morik
2020 J jnl
Resource-Constrained On-Device Learning by Dynamic Averaging.
CoRR
Lukas Heppe, Michael Kamp, Linara Adilova, Danny Heinrich, Nico Piatkowski, Katharina Morik
2019 J jnl
A Reparameterization-Invariant Flatness Measure for Deep Neural Networks.
CoRR
Henning Petzka, Linara Adilova, Michael Kamp, Cristian Sminchisescu
2019 J jnl
Information-Theoretic Perspective of Federated Learning.
CoRR
Linara Adilova, Julia Rosenzweig, Michael Kamp
2019 — conf
System Misuse Detection Via Informed Behavior Clustering and Modeling.
DSN Workshops
Linara Adilova, Livin Natious, Siming Chen, Olivier Thonnard, Michael Kamp
2019 J jnl
System Misuse Detection via Informed Behavior Clustering and Modeling.
CoRR
Linara Adilova, Livin Natious, Siming Chen, Olivier Thonnard, Michael Kamp
2018 — conf
Efficient Decentralized Deep Learning by Dynamic Model Averaging.
ECML/PKDD (1)
Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel
2018 J jnl
Efficient Decentralized Deep Learning by Dynamic Model Averaging.
CoRR
Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel
2018 — conf
Introducing Noise in Decentralized Training of Neural Networks.
DMLE/IOTSTREAMING@PKDD/ECML
Linara Adilova, Nathalie Paul, Peter Schlicht
2018 J jnl
Introducing Noise in Decentralized Training of Neural Networks.
CoRR
Linara Adilova, Nathalie Paul, Peter Schlicht
2018 J jnl
Making Efficient Use of a Domain Expert's Time in Relation Extraction.
CoRR
Linara Adilova, Sven Giesselbach, Stefan Rüping