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PKDD/ECML 2021: Bilbao, Spain (Virtual Event) - Workshops
- Michael Kamp
, Irena Koprinska
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. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5
Advances in Interpretable Machine Learning and Artificial Intelligence
- Udo Schlegel, Duy Vo Lam, Daniel A. Keim, Daniel Seebacher:
TS-MULE: Local Interpretable Model-Agnostic Explanations for Time Series Forecast Models. 5-14 - Troy Maasland, João Pereira, Diogo Bastos, Marcus de Goffau, Max Nieuwdorp, Aeilko H. Zwinderman, Evgeni Levin:
Interpretable Models via Pairwise Permutations Algorithm. 15-25 - Véronne Yepmo Tchaghe, Grégory Smits, Olivier Pivert:
A Classification of Anomaly Explanation Methods. 26-33 - Andrew Yeh, Anhthy Ngo:
Bringing a Ruler Into the Black Box: Uncovering Feature Impact from Individual Conditional Expectation Plots. 34-48 - Maxence Queyrel, Alexandre Templier, Jean-Daniel Zucker:
Reject and Cascade Classifier with Subgroup Discovery for Interpretable Metagenomic Signatures. 49-66 - Anna Himmelhuber, Mitchell Joblin, Martin Ringsquandl, Thomas A. Runkler:
Demystifying Graph Neural Network Explanations. 67-75 - Safa Alsaidi
On the Transferability of Neural Models of Morphological Analogies. 76-89 - Chhavi Yadav, Kamalika Chaudhuri:
Behavior of k-NN as an Instance-Based Explanation Method. 90-96 - Hamed Behzadi Khormuji
Enhancing Performance of Occlusion-Based Explanation Methods by a Hierarchical Search Method on Input Images. 97-104 - Victor Guyomard, Françoise Fessant, Tassadit Bouadi, Thomas Guyet
Post-hoc Counterfactual Generation with Supervised Autoencoder. 105-114
Parallel, Distributed, and Federated Learning
- Timon Sachweh
Differentially Private Learning from Label Proportions. 119-127 - Florian Linsner, Linara Adilova, Sina Däubener, Michael Kamp, Asja Fischer:
Approaches to Uncertainty Quantification in Federated Deep Learning. 128-145 - Yongli Mou, Jiahui Geng, Sascha Welten, Chunming Rong
Optimized Federated Learning on Class-Biased Distributed Data Sources. 146-158 - Saber Malekmohammadi, Kiarash Shaloudegi, Zeou Hu, Yaoliang Yu:
Splitting Algorithms for Federated Learning. 159-176 - Péter Kiss
Migrating Models: A Decentralized View on Federated Learning. 177-191
Graph Embedding and Mining
- Tobias Schumacher
The Effects of Randomness on the Stability of Node Embeddings. 197-215 - Paul Beaujean, Florian Sikora, Florian Yger:
Graph Homomorphism Features: Why Not Sample? 216-222 - Thomas Pontoizeau, Florian Sikora, Florian Yger, Tristan Cazenave:
Neural Maximum Independent Set. 223-237 - Jiaqing Xie
Fea2Fea: Exploring Structural Feature Correlations via Graph Neural Networks. 238-257 - Chen Dang, Hicham Randrianarivo, Raphaël Fournier-S'niehotta, Nicolas Audebert:
Web Image Context Extraction with Graph Neural Networks and Sentence Embeddings on the DOM Tree. 258-267 - Tomas Martin, Victor Fuentes, Petko Valtchev, Abdoulaye Baniré Diallo, René Lacroix, Maxime Leduc, Mounir Boukadoum:
Towards Mining Generalized Patterns from RDF Data and a Domain Ontology. 268-278
Machine Learning for Irregular Time Series
- Luciano Melodia
Homological Time Series Analysis of Sensor Signals from Power Plants. 283-299 - Mona Schirmer, Mazin Eltayeb, Maja Rudolph:
Continuous-Discrete Recurrent Kalman Networks for Irregular Time Series. 300-305 - Ankur Debnath, Nitish Gupta, Govind Waghmare, Hardik Wadhwa, Siddhartha Asthana, Ankur Arora:
Adversarial Generation of Temporal Data: A Critique on Fidelity of Synthetic Data. 306-321
IoT, Edge, and Mobile for Embedded Machine Learning
- Lukas Einhaus, Chao Qian, Christopher Ringhofer, Gregor Schiele:
Towards Precomputed 1D-Convolutional Layers for Embedded FPGAs. 327-338 - Iris Walter
Embedded Face Recognition for Personalized Services in the Assistive Robotics. 339-350 - Hassan Ghasemzadeh Mohammadi, Felix Paul Jentzsch, Maurice Kuschel, Rahil Arshad, Sneha Rautmare, Suraj Manjunatha, Marco Platzner, Alexander Boschmann, Dirk Schollbach:
FLight: FPGA Acceleration of Lightweight DNN Model Inference in Industrial Analytics. 351-362 - Ilja van Ipenburg, Dolly Sapra
Exploring Cell-Based Neural Architectures for Embedded Systems. 363-374 - Armin Schuster, Christian Heidorn, Marcel Brand, Oliver Keszöcze, Jürgen Teich:
Design Space Exploration of Time, Energy, and Error Rate Trade-offs for CNNs Using Accuracy-Programmable Instruction Set Processors. 375-389 - Sven Nitzsche
Ultra-low Power Machinery Fault Detection Using Deep Neural Networks. 390-396 - Lukas Sommer
SPNC: Fast Sum-Product Network Inference. 397-408 - Bernhard Klein
Towards Addressing Noise and Static Variations of Analog Computations Using Efficient Retraining. 409-420
eXplainable Knowledge Discovery in Data Mining
- Andreas Holzinger
The Next Frontier: AI We Can Really Trust. 427-440 - Meike Nauta, Annemarie Jutte
This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition. 441-456 - Kamil Plucinski, Mateusz Lango
Prototypical Convolutional Neural Network for a Phrase-Based Explanation of Sentiment Classification. 457-472 - Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Explanations for Network Embedding-Based Link Predictions. 473-488 - Suryabhan Singh Hada
Exploring Counterfactual Explanations for Classification and Regression Trees. 489-504 - Katarzyna Woznica
Towards Explainable Meta-learning. 505-520 - Tom Vermeire, Thibault Laugel, Xavier Renard, David Martens, Marcin Detyniecki:
How to Choose an Explainability Method? Towards a Methodical Implementation of XAI in Practice. 521-533 - Zhi Chen, Sarah Tan, Harsha Nori, Kori Inkpen, Yin Lou, Rich Caruana:
Using Explainable Boosting Machines (EBMs) to Detect Common Flaws in Data. 534-551
Bias and Fairness in AI
- William Blanzeisky, Pádraig Cunningham
Algorithmic Factors Influencing Bias in Machine Learning. 559-574 - Carlos Mougan Navarro, Georgios Kanellos, Thomas Gottron:
Desiderata for Explainable AI in Statistical Production Systems of the European Central Bank. 575-590 - Serafina Kamp
Robustness of Fairness: An Experimental Analysis. 591-606 - Gabriel Frisch, Jean-Benoist Léger, Yves Grandvalet:
Co-clustering for Fair Recommendation. 607-630 - Daphne Lenders
Learning a Fair Distance Function for Situation Testing. 631-646 - Alessandro Castelnovo
Towards Fairness Through Time. 647-663
International Workshop on Active Inference
- Aswin Paul
Active Inference for Stochastic Control. 669-680 - Mohamed Baioumy, Corrado Pezzato
Towards Stochastic Fault-Tolerant Control Using Precision Learning and Active Inference. 681-691 - Ajith Anil Meera, Martijn Wisse
On the Convergence of DEM's Linear Parameter Estimator. 692-700 - Toon Van de Maele, Tim Verbelen, Ozan Çatal, Bart Dhoedt:
Disentangling What and Where for 3D Object-Centric Representations Through Active Inference. 701-714 - Tore Erdmann, Christoph Mathys:
Rule Learning Through Active Inductive Inference. 715-725 - Nathaniel Virgo
Interpreting Dynamical Systems as Bayesian Reasoners. 726-762 - Morten Henriksen
Blankets All the Way up - the Economics of Active Inference. 763-771 - Ben White, Mark Miller:
Filtered States: Active Inference, Social Media and Mental Health. 772-783 - Natalie Kastel, Casper Hesp
Ideas Worth Spreading: A Free Energy Proposal for Cumulative Cultural Dynamics. 784-798 - Adam Safron
Dream to Explore: 5-HT2a as Adaptive Temperature Parameter for Sophisticated Affective Inference. 799-809 - Peter Thestrup Waade
Inferring in Circles: Active Inference in Continuous State Space Using Hierarchical Gaussian Filtering of Sufficient Statistics. 810-818 - Mohamed Baioumy, Bruno Lacerda, Paul Duckworth, Nick Hawes:
On Solving a Stochastic Shortest-Path Markov Decision Process as Probabilistic Inference. 819-829 - Paul F. Kinghorn, Beren Millidge, Christopher L. Buckley:
Habitual and Reflective Control in Hierarchical Predictive Coding. 830-842 - Niels van Hoeffelen, Pablo Lanillos:
Deep Active Inference for Pixel-Based Discrete Control: Evaluation on the Car Racing Problem. 843-856 - Daniel Burghardt, Pablo Lanillos:
Robot Localization and Navigation Through Predictive Processing Using LiDAR. 857-864 - Kanako Esaki
Sensorimotor Visual Perception on Embodied System Using Free Energy Principle. 865-877
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