newsitem: ECML PKDD 2024
Our cluster will be greatly represented at this year’s European Conference on Machine Learning and Data Mining (ECML-PKDD)! There are no less than 11 opportunities to meet / read from / listen to our members:
Research Track
Probabilistic Circuits with Constraints via Convex Optimization by Soroush Ghandi (TU/e)*; Benjamin Quost (Université de Technologie de Compiègne); Cassio de Campos (TU/e)
Adaptive Sparsity Level during Training for Efficient Time Series Forecasting with Transformers by Zahra Atashgahi (University of Twente)*; Mykola Pechenizkiy (TU/e); Raymond Veldhuis (University of Twente); Decebal Constantin Mocanu (University of Luxembourg)
ADS Track
Bandits for Sponsored Search Auctions under Unknown Valuation Model: Case Study in E-Commerce Advertising by Danil Provodin (TU/e)*; Jeremie Joudioux (Zalando SE); Eduard Duryev (Zalando SE)
Exceptional Subitizing Range: Exploring Mathematical Abilities of Finnish Primary School Children with Piecewise Linear Regression by Rianne M Schouten (TU/e)*; Wouter Duivesteijn (TU/e); Pekka J. Rasanen (Turku Research Institute for Learning Analytics); Jacob Paul (The University of Melbourne); Mykola Pechenizkiy (TU/e)
Nectar track
Algorithmic Unfairness through the Lens of EU Non-Discrimination Law (Or Why the Law is Not a Decision Tree) by Hilde JP Weerts (TU/e)*; Mykola Pechenizkiy (TU/e)
Demo track
Subgroup Harm Assessor: Identifying Potential Fairness-Related Harms and Predictive Bias by Adam Dubowski (TU/e)*; Hilde JP Weerts (TU/e); Anouk Wolters (Deeploy); Mykola Pechenizkiy (TU/e)
Journal track
Towards Efficient AutoML: A Pipeline Synthesis Approach Leveraging Pre-Trained Transformers for Multimodal Data By Ambarish S. Moharil (TU/e), Joaquin Vanschoren (TU/e), Prabhant Singh (TU/e), Damian Tamburri (JADS)
BIAS workshop - co-organized by Hilde Weerts
Everyone deserves their voice to be heard: Analyzing Predictive Bias in ASR Models Applied to Dutch Speech Data by Rik Raes (TU/e)*; Saskia E Lensink (TNO); Mykola Pechenizkiy (TU/e)
RKDE workshop
Keynote: Title Benchmarking and Reasoning about Fairness in Machine Learning by Mykola Pechenizkiy
ML4SPS workshop
Achieving Long-term Time Series Forecasting Models with Fewer Than 1k Parameters through Dynamic Sparse Training by Qiao Xiao (TU/e)*; Mykola Pechenizkiy (TU/e); Decebal Constantin Mocanu (University of Luxembourg)
PhD Forum
Learning efficiency with sparsity: from model to data, and to communication by Qiao Xiao (TU/e)*; Boqian Wu (University of Twente), Mykola Pechenizkiy (TU/e); Decebal Constantin Mocanu (University of Luxembourg)