Machine Learning

Papers
(The H4-Index of Machine Learning is 28. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-03-01 to 2025-03-01.)
ArticleCitations
Lifted model checking for relational MDPs799
SA-LfV: self-annotated labeling from videos for object detection225
Learning multi-axis representation in frequency domain for medical image segmentation171
PerfoRank: cluster-based performance ranking for improved performance evaluation and estimation in professional cycling105
Credal ensembling in multi-class classification96
Resolving power: a general approach to compare the distinguishing ability of threshold-free evaluation metrics92
Misclassification bounds for PAC-Bayesian sparse deep learning79
Dealing with the unevenness: deeper insights in graph-based attack and defense77
Speeding up neural network robustness verification via algorithm configuration and an optimised mixed integer linear programming solver portfolio67
Semi-supervised Latent Block Model with pairwise constraints64
Moreau-Yoshida variational transport: a general framework for solving regularized distributional optimization problems58
Correction to: Deep negative correlation classification57
Assessing machine learning and data imputation approaches to handle the issue of data sparsity in sports forecasting53
De-biased two-sample U-statistics with application to conditional distribution testing48
Adapting performance metrics for ordinal classification to interval scale: length matters45
Maximum causal entropy inverse constrained reinforcement learning44
Explanatory machine learning for sequential human teaching39
PAC-learning with approximate predictors39
Bayesian optimization with approximate set kernels38
Reachable sets of classifiers and regression models: (non-)robustness analysis and robust training36
Are LSTMs good few-shot learners?36
Multi-objective multi-armed bandit with lexicographically ordered and satisficing objectives35
Multiclass optimal classification trees with SVM-splits35
No regret sample selection with noisy labels32
GS2P: a generative pre-trained learning to rank model with over-parameterization for web-scale search32
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations30
Machine learning in corporate credit rating assessment using the expanded audit report30
Recursive tree grammar autoencoders28
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