"Statistical methods utilizing structural properties of time-evolving networks for event detection" by Monika Bansal & Dolly Sharma (link.springer.com/article/10.100…)

#DAMI, #OA, read it! 🙂"Discord-based counterfactual explanations for time series classification" by Omar Bahri, Peiyu Li, Soukaina Filali Boubrahimi & Shah Muhammad Hamdi (link.springer.com/article/10.100…)

"ArcMatch: high-performance subgraph matching for labeled graphs by exploiting edge domains" by Vincenzo Bonnici, Roberto Grasso, Giovanni Micale, Antonio di Maria, Dennis Shasha, Alfredo Pulvirenti & Rosalba Giugno (link.springer.com/article/10.100…) #OA

"On regime changes in text data using hidden Markov model of contaminated vMF distribution" by Yingying Zhang, Shuchismita Sarkar, Yuanyuan Chen & Xuwen Zhu (link.springer.com/article/10.100…)

"Sequential query prediction based on multi-armed bandits with ensemble of transformer experts and immediate feedback" by Shameem A. Puthiya Parambath, Christos Anagnostopoulos & Roderick Murray-Smith (link.springer.com/article/10.100…) #OA

Great quick survey and open access to boot: "Explainable and interpretable machine learning and data mining" by Martin Atzmüller, Johannes Fürnkranz, Tomáš Kliegr & Ute Schmid (link.springer.com/article/10.100…) #OA

"Gradient-based explanation for non-linear non-parametric dimensionality reduction" by Sacha Corbugy, Rebecca Marion & Benoît Frénay (link.springer.com/article/10.100…)

"De-confounding representation learning for counterfactual inference on continuous treatment via generative adversarial network" by Yonghe Zhao, Qiang Huang, Haolong Zeng, Yun Peng & Huiyan Sun (link.springer.com/article/10.100…)

"Enhancing racism classification: an automatic multilingual data annotation system using self-training and CNN" by Ikram El Miqdadi, Soufiane Hourri, Fatima Zahra El Idrysy, Assia Hayati, Yassine Namir, Nikola S. Nikolov & Jamal Kharroubi (link.springer.com/article/10.100…)

Another ECML PKDD 2024 (in two weeks) journal track (link.springer.com/collections/da…) paper: "Explainable decomposition of nested dense subgraphs" by Nikolaj Tatti. And open access: link.springer.com/article/10.100… #OA

"Negative-sample-free knowledge graph embedding" by Adil Bahaj & Mounir Ghogho (link.springer.com/article/10.100…)

You wouldn't know it from the title of this #DAMI paper but it's about ensemble learning: "Deep negative correlation classification" by Le Zhang, Qibin Hou, Yun Liu, Jia-Wang Bian, Xun Xu, Joey Tianyi Zhou & Ce Zhu (link.springer.com/article/10.100…), and it sounds very interesting!

New week and we just keep going with #DAMI online-first articles: "Efficient learning with projected histograms" by Zhanliang Huang, Ata Kabán & Henry Reeve (link.springer.com/article/10.100…) #OA

"Opinion dynamics in social networks incorporating higher-order interactions" by Zuobai Zhang, Wanyue Xu, Zhongzhi Zhang & Guanrong Chen (link.springer.com/article/10.100…)

"Model-agnostic variable importance for predictive uncertainty: an entropy-based approach" by Danny Wood, Theodore Papamarkou, Matt Benatan & Richard Allmendinger. Another open access one: link.springer.com/article/10.100… #OA

New open-access online-first #DAMI paper: "Evaluating the disclosure risk of anonymized documents via a machine learning-based re-identification attack" by Benet Manzanares-Salor, David Sánchez & Pierre Lison (link.springer.com/article/10.100…) #OA

"Bounding the family-wise error rate in local causal discovery using Rademacher averages" by Dario Simionato & Fabio Vandin (link.springer.com/article/10.100…) open access! #OA

I don't know where they found the "R" in "FRUITS" but great title: "FRUITS: feature extraction using iterated sums for time series classification" by Joscha Diehl & Richard Krieg, and open access to boot: link.springer.com/article/10.100…