ECML PKDD 2025

by invitation only

Journal

Machine Learning

Machine Learning is an international forum focusing on computational approaches to learning.

Concha Bielza

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Ana Carolina Lorena

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Arlindo Oliveira

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Longbing Cao

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Tiago Almeida

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Showing 1-24 of 24 articles

Linearly-interpretable concept embedding models for text analysis
Francesco De Santis
Philippe Bich
Tania Cerquitelli
OriginalPaper Open access 04 September 2025 Article: 224
TFAS: zero-shot NAS for general time-series analysis with time-frequency aware scoring
Patara Trirat
Jae-Gil Lee
OriginalPaper 29 August 2025 Article: 223
Pasco (PArallel Structured COarsening): an overlay to speed up graph clustering algorithms
Lasalle Etienne
Vaudaine Rémi
Karsai Márton
OriginalPaper 22 August 2025 Article: 212
Learning Green’s function efficiently using low-rank approximations
Kishan Wimalawarne
Taiji Suzuki
Sophie Langer
OriginalPaper 22 August 2025 Article: 214
ALM-PU: positive and unlabeled learning with constrained optimization
Jiazhe Wei
Yuefei Wu
Bo Dong
OriginalPaper 20 August 2025 Article: 210
Uncover and unlearn nuisances: agnostic fully test-time adaptation
Ponhvoan Srey
Yaxin Shi
Ivor W. Tsang
OriginalPaper 06 August 2025 Article: 203
A calibration test for evaluating set-based epistemic uncertainty representations
Mira Jürgens
Thomas Mortier
Willem Waegeman
OriginalPaper Open access 05 August 2025 Article: 202
Achieving collective welfare in multi-agent reinforcement learning via suggestion sharing
Yue Jin
Shuangqing Wei
Giovanni Montana
OriginalPaper Open access 15 July 2025 Article: 190
Offline reinforcement learning for learning to dispatch for job shop scheduling
Jesse van Remmerden
Zaharah Bukhsh
Yingqian Zhang
OriginalPaper Open access 15 July 2025 Article: 191
Robust partial-label learning by leveraging class activation values
Tobias Fuchs
Florian Kalinke
OriginalPaper Open access 15 July 2025 Article: 193
Perfect counterfactuals in imperfect worlds: modelling noisy implementation of actions in sequential algorithmic recourse
Yueqing Xuan
Kacper Sokol
Jeffrey Chan
OriginalPaper Open access 13 July 2025 Article: 187
Search or split: policy gradient with adaptive policy space
Gianmarco Tedeschi
Matteo Papini
Marcello Restelli
OriginalPaper 11 July 2025 Article: 186
Analyzing the effect of residual connections to oversmoothing in graph neural networks
Dimitrios Kelesis
Dimitris Fotakis
Georgios Paliouras
OriginalPaper Open access 11 July 2025 Article: 184
Single image inpainting and super-resolution with simultaneous uncertainty guarantees by universal reproducing kernels
Bálint Horváth
Balázs Csanád Csáji
OriginalPaper Open access 10 July 2025 Article: 179
TransFed: cross-domain feature alignment for semi-supervised federated transfer learning
Linghui Zeng
Ruixuan Liu
Joyce C. Ho
OriginalPaper 10 July 2025 Article: 181
Improving graph neural networks through feature importance learning
Fouad Alkhoury
Tamás Horváth
Stefan Wrobel
OriginalPaper Open access 24 June 2025 Article: 178
JANET: Joint Adaptive predictioN-region Estimation for Time-series
Eshant English
Eliot Wong-Toi
Christoph Lippert
ReviewPaper Open access 23 June 2025 Article: 177
MUSO: achieving exact machine unlearning in over-parameterized regimes
Ruikai Yang
Mingzhen He
Xiaolin Huang
OriginalPaper 20 June 2025 Article: 176
Efficient and interpretable raw audio classification with diagonal state space models
Matthias Bittner
Daniel Schnöll
Axel Jantsch
OriginalPaper Open access 19 June 2025 Article: 175
HE-GAD: a behavior-enhanced contrastive learning framework for graph anomaly detection
Ling Zheng
Qi Song
Xiangyang Li
OriginalPaper 17 June 2025 Article: 169
Fedflow: a personalized federated learning framework for passenger flow prediction
Franca Rocco di Torrepadula
Marco Fisichella
Nicola Mazzocca
OriginalPaper Open access 11 June 2025 Article: 166
Jensen–Tsallis divergence for supervised classification under data imbalance
Antonio Squicciarini
Tom Trigano
David Luengo
OriginalPaper Open access 05 June 2025 Article: 162
Navigating explanatory multiverse through counterfactual path geometry
Kacper Sokol
Edward Small
Yueqing Xuan
OriginalPaper Open access 28 April 2025 Article: 144
Drop-in efficient self-attention approximation method
Damien François
Mathis Saillot
Alexander Skupin
OriginalPaper Open access 24 April 2025 Article: 139

ECML PKDD 2025

Participating journal

Machine Learning

Editors

Concha Bielza

Ana Carolina Lorena

Arlindo Oliveira

Longbing Cao

Tiago Almeida

Articles

Linearly-interpretable concept embedding models for text analysis

TFAS: zero-shot NAS for general time-series analysis with time-frequency aware scoring

Pasco (PArallel Structured COarsening): an overlay to speed up graph clustering algorithms

Learning Green’s function efficiently using low-rank approximations

ALM-PU: positive and unlabeled learning with constrained optimization

Uncover and unlearn nuisances: agnostic fully test-time adaptation

A calibration test for evaluating set-based epistemic uncertainty representations

Achieving collective welfare in multi-agent reinforcement learning via suggestion sharing

Offline reinforcement learning for learning to dispatch for job shop scheduling

Robust partial-label learning by leveraging class activation values

Perfect counterfactuals in imperfect worlds: modelling noisy implementation of actions in sequential algorithmic recourse

Search or split: policy gradient with adaptive policy space

Analyzing the effect of residual connections to oversmoothing in graph neural networks

Single image inpainting and super-resolution with simultaneous uncertainty guarantees by universal reproducing kernels

TransFed: cross-domain feature alignment for semi-supervised federated transfer learning

Improving graph neural networks through feature importance learning

JANET: Joint Adaptive predictioN-region Estimation for Time-series

MUSO: achieving exact machine unlearning in over-parameterized regimes

Efficient and interpretable raw audio classification with diagonal state space models

HE-GAD: a behavior-enhanced contrastive learning framework for graph anomaly detection

Fedflow: a personalized federated learning framework for passenger flow prediction

Jensen–Tsallis divergence for supervised classification under data imbalance

Navigating explanatory multiverse through counterfactual path geometry

Drop-in efficient self-attention approximation method