---
title: "Machine Learning 2023 — all accepted papers — Elamur Research"
description: "All 203 papers of Machine Learning 2023 · page 1 of 3, the most cited first; those with our summary link to it."
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# Machine Learning 2023: all accepted papers

203 papers · page 1 of 3 · the most cited first · [← Machine Learning 2023](https://md.research.elamur.ai/free/en/venues/machine-learning/2023/)

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1. **[A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning ↗](https://doi.org/10.1007/s10994-022-06296-4)**Dina Elreedy, Amir F. Atiya, Firuz Kamalov*388 citations*
2. **[Classifier calibration: a survey on how to assess and improve predicted class probabilities ↗](https://doi.org/10.1007/s10994-023-06336-7)**Telmo M. Silva Filho, Hao Song, Miquel Perelló-Nieto et al.*211 citations*
3. **[A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework ↗](https://doi.org/10.1007/s10994-023-06353-6)**Gabriel Aguiar, Bartosz Krawczyk, Alberto Cano*164 citations*
4. **[Domain adversarial neural networks for domain generalization: when it works and how to improve ↗](https://doi.org/10.1007/s10994-023-06324-x)**Anthony Sicilia, Xingchen Zhao, Seong Jae Hwang*134 citations*
5. **[Active learning for data streams: a survey ↗](https://doi.org/10.1007/s10994-023-06454-2)**Davide Cacciarelli, Murat Külahçı*110 citations*
6. **[On the sample complexity of actor-critic method for reinforcement learning with function approximation ↗](https://doi.org/10.1007/s10994-023-06303-2)**Harshat Kumar, Alec Koppel, Alejandro Ribeiro*70 citations*
7. **[Understanding CNN fragility when learning with imbalanced data ↗](https://doi.org/10.1007/s10994-023-06326-9)**Damien A. Dablain, Kristen N. Jacobson, Colin Bellinger et al.*69 citations*
8. **[Fraud detection with natural language processing ↗](https://doi.org/10.1007/s10994-023-06354-5)**Petros Boulieris, John Pavlopoulos, Alexandros Xenos et al.*57 citations*
9. **[Incremental permutation feature importance (iPFI): towards online explanations on data streams ↗](https://doi.org/10.1007/s10994-023-06385-y)**Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier et al.*54 citations*
10. **[Deep reinforcement learning for multi-class imbalanced training: applications in healthcare ↗](https://doi.org/10.1007/s10994-023-06481-z)**Jenny Yang, Rasheed El-Bouri, Odhran O’Donoghue et al.*53 citations*
11. **[Explainable reinforcement learning (XRL): a systematic literature review and taxonomy ↗](https://doi.org/10.1007/s10994-023-06479-7)**Yanzhe Bekkemoen*51 citations*
12. **[Libsignal: an open library for traffic signal control ↗](https://doi.org/10.1007/s10994-023-06412-y)**Hao Mei, Xiaoliang Lei, Longchao Da et al.*47 citations*
13. **[WEASEL 2.0: a random dilated dictionary transform for fast, accurate and memory constrained time series classification ↗](https://doi.org/10.1007/s10994-023-06395-w)**Patrick Schäfer, Ulf Leser*47 citations*
14. **[Deep learning’s shallow gains: a comparative evaluation of algorithms for automatic music generation ↗](https://doi.org/10.1007/s10994-023-06309-w)**Zongyu Yin, Federico Reuben, Susan Stepney et al.*44 citations*
15. **[Explainable AI in drug discovery: self-interpretable graph neural network for molecular property prediction using concept whitening ↗](https://doi.org/10.1007/s10994-023-06369-y)**Michela Proietti, Alessio Ragno, Biagio La Rosa et al.*44 citations*
16. **[A survey of class-imbalanced semi-supervised learning ↗](https://doi.org/10.1007/s10994-023-06344-7)**Qian Gui, Zhou Hong, Na Guo et al.*43 citations*
17. **[Temporal graph learning for dynamic link prediction with text in online social networks ↗](https://doi.org/10.1007/s10994-023-06475-x)**Manuel Dileo, Matteo Zignani, Sabrina Gaito*38 citations*
18. **[Generation, augmentation, and alignment: a pseudo-source domain based method for source-free domain adaptation ↗](https://doi.org/10.1007/s10994-023-06432-8)**Yuntao Du, Haiyang Yang, Mingcai Chen et al.*37 citations*
19. **[Chinese character recognition with radical-structured stroke trees ↗](https://doi.org/10.1007/s10994-023-06450-6)**Haiyang Yu, Jingye Chen, Bin Li et al.*34 citations*
20. **[Considerations when learning additive explanations for black-box models ↗](https://doi.org/10.1007/s10994-023-06335-8)**Sarah Tan, Giles Hooker, Paul Koch et al.*33 citations*
21. **[Targeted adversarial attacks on wind power forecasts ↗](https://doi.org/10.1007/s10994-023-06396-9)**René Heinrich, Christoph Scholz, Stephan Vogt et al.*32 citations*
22. **[Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning ↗](https://doi.org/10.1007/s10994-023-06422-w)**Ramij Raja Hossain, Tianzhixi Yin, Yan Du et al.*31 citations*
23. **[PreCoF: counterfactual explanations for fairness ↗](https://doi.org/10.1007/s10994-023-06319-8)**Sofie Goethals, David Martens, Toon Calders*31 citations*
24. **[Manas: multi-agent neural architecture search ↗](https://doi.org/10.1007/s10994-023-06379-w)**Vasco Lopes, Fabio Maria Carlucci, Pedro M. Esperança et al.*30 citations*
25. **[Interpreting machine-learning models in transformed feature space with an application to remote-sensing classification ↗](https://doi.org/10.1007/s10994-023-06327-8)**Alexander Brenning*29 citations*
26. **[Deep multimodal representation learning for generalizable person re-identification ↗](https://doi.org/10.1007/s10994-023-06352-7)**Suncheng Xiang, Hao Chen, Ran Wei et al.*28 citations*
27. **[Ensemble and continual federated learning for classification tasks ↗](https://doi.org/10.1007/s10994-023-06330-z)**Fernando E. Casado, Dylan Lema, Roberto Iglesias et al.*28 citations*
28. **[Graph similarity learning for change-point detection in dynamic networks ↗](https://doi.org/10.1007/s10994-023-06405-x)**Déborah Sulem, Henry Kenlay, Mihai Cucuringu et al.*27 citations*
29. **[UCoDe: unified community detection with graph convolutional networks ↗](https://doi.org/10.1007/s10994-023-06402-0)**Atefeh Moradan, Andrew Draganov, Davide Mottin et al.*27 citations*
30. **[Hyperparameter importance and optimization of quantum neural networks across small datasets ↗](https://doi.org/10.1007/s10994-023-06389-8)**Charles Moussa, Yash J. Patel, Vedran Dunjko et al.*25 citations*
31. **[Robust federated learning under statistical heterogeneity via hessian-weighted aggregation ↗](https://doi.org/10.1007/s10994-022-06292-8)**Adnan Ahmad, Wei Luo, Antonio Robles‐Kelly*24 citations*
32. **[Robust generative adversarial network ↗](https://doi.org/10.1007/s10994-023-06367-0)**Shufei Zhang, Zhuang Qian, Kaizhu Huang et al.*24 citations*
33. **[Hybrid acceleration techniques for the physics-informed neural networks: a comparative analysis ↗](https://doi.org/10.1007/s10994-023-06442-6)**F. A. Buzaev, Jiexing Gao, I. A. Chuprov et al.*22 citations*
34. **[GMMSampling: a new model-based, data difficulty-driven resampling method for multi-class imbalanced data ↗](https://doi.org/10.1007/s10994-023-06416-8)**Iwo Naglik, Mateusz Lango*21 citations*
35. **[ROAD-R: the autonomous driving dataset with logical requirements ↗](https://doi.org/10.1007/s10994-023-06322-z)**Eleonora Giunchiglia, Mihaela Cătălina Stoian, Salman S. Khan et al.*21 citations*
36. **[\alphaILP: thinking visual scenes as differentiable logic programs ↗](https://doi.org/10.1007/s10994-023-06320-1)**Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami et al.*21 citations*
37. **[Efficient generator of mathematical expressions for symbolic regression ↗](https://doi.org/10.1007/s10994-023-06400-2)**Sebastian Mežnar, Sašo Džeroski, Ljupčo Todorovski*20 citations*
38. **[FFNSL: Feed-Forward Neural-Symbolic Learner ↗](https://doi.org/10.1007/s10994-022-06278-6)**Daniel Cunnington, Mark Law, Jorge Lobo et al.*19 citations*
39. **[Efficient learning of large sets of locally optimal classification rules ↗](https://doi.org/10.1007/s10994-022-06290-w)**Van Quoc Phuong Huynh, Johannes Fürnkranz, Florian Beck*17 citations*
40. **[Natural language inference model for customer advocacy detection in online customer engagement ↗](https://doi.org/10.1007/s10994-023-06476-w)**Bilal Abu-Salih, Mohammed Alweshah, Moutaz Alazab et al.*17 citations*
41. **[Contrastive counterfactual visual explanations with overdetermination ↗](https://doi.org/10.1007/s10994-023-06333-w)**Adam White, Kwun Ho Ngan, James Phelan et al.*16 citations*
42. **[Explaining recommendation system using counterfactual textual explanations ↗](https://doi.org/10.1007/s10994-023-06390-1)**Niloofar Ranjbar, Saeedeh Momtazi, MohammadMehdi Homayoonpour*16 citations*
43. **[Learning system parameters from turing patterns ↗](https://doi.org/10.1007/s10994-023-06334-9)**David Schnoerr, Christoph Schnörr*16 citations*
44. **[Generalizing universal adversarial perturbations for deep neural networks ↗](https://doi.org/10.1007/s10994-023-06306-z)**Yanghao Zhang, Wenjie Ruan, Fu Wang et al.*15 citations*
45. **[Multiclass optimal classification trees with SVM-splits ↗](https://doi.org/10.1007/s10994-023-06366-1)**Víctor Blanco, Alberto Japón, Justo Puerto*15 citations*
46. **[Persian offensive language detection ↗](https://doi.org/10.1007/s10994-023-06370-5)**Emad Kebriaei, Ali Homayouni, Roghayeh Faraji et al.*15 citations*
47. **[SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting ↗](https://doi.org/10.1007/s10994-023-06316-x)**Rakshitha Godahewa, Geoffrey I. Webb, Daniel Francis Schmidt et al.*15 citations*
48. **[A geometric framework for multiclass ensemble classifiers ↗](https://doi.org/10.1007/s10994-023-06406-w)**Shengli Wu, Jinlong Li, Weimin Ding*14 citations*
49. **[Cost-sensitive sparse group online learning for imbalanced data streams ↗](https://doi.org/10.1007/s10994-023-06403-z)**Zhong Chen, Victor S. Sheng, Andrea Edwards et al.*14 citations*
50. **[Federated learning with superquantile aggregation for heterogeneous data ↗](https://doi.org/10.1007/s10994-023-06332-x)**Krishna Pillutla, Yassine Laguel, Jérôme Malick et al.*14 citations*
51. **[Composite score for anomaly detection in imbalanced real-world industrial dataset ↗](https://doi.org/10.1007/s10994-023-06415-9)**Arnaud Bougaham, Mohammed El Adoui, Isabelle Linden et al.*13 citations*
52. **[How to be fair? A study of label and selection bias ↗](https://doi.org/10.1007/s10994-023-06401-1)**Marco Favier, Toon Calders, Sam Pinxteren et al.*13 citations*
53. **[Understanding transfer learning and gradient-based meta-learning techniques ↗](https://doi.org/10.1007/s10994-023-06387-w)**Mike Huisman, Aske Plaat, Jan N. van Rijn*13 citations*
54. **[Are LSTMs good few-shot learners? ↗](https://doi.org/10.1007/s10994-023-06394-x)**Mike Huisman, Thomas M. Moerland, Aske Plaat et al.*12 citations*
55. **[FAC-fed: Federated adaptation for fairness and concept drift aware stream classification ↗](https://doi.org/10.1007/s10994-023-06360-7)**Maryam Badar, Wolfgang Nejdl, Marco Fisichella*12 citations*
56. **[Hellinger distance decision trees for PU learning in imbalanced data sets ↗](https://doi.org/10.1007/s10994-023-06323-y)**Carlos Ortega Vázquez, Seppe vanden Broucke, Jochen De Weerdt*12 citations*
57. **[Multi-armed bandits with dependent arms ↗](https://doi.org/10.1007/s10994-023-06457-z)**Rahul Singh, Fang Liu, Yin Jian Sun et al.*12 citations*
58. **[Multi-label image classification with multi-layered multi-perspective dynamic semantic representation ↗](https://doi.org/10.1007/s10994-023-06440-8)**Wenlan Kuang, Zhixin Li*12 citations*
59. **[Solving imbalanced learning with outlier detection and features reduction ↗](https://doi.org/10.1007/s10994-023-06448-0)**Salvatore Lusito, Andrea Pugnana, Riccardo Guidotti*12 citations*
60. **[Synthesizing explainable counterfactual policies for algorithmic recourse with program synthesis ↗](https://doi.org/10.1007/s10994-022-06293-7)**Giovanni De Toni, Bruno Lepri, Andrea Passerini*12 citations*
61. **[Correlated product of experts for sparse Gaussian process regression ↗](https://doi.org/10.1007/s10994-022-06297-3)**Manuel Schürch, Dario Azzimonti, Alessio Benavoli et al.*11 citations*
62. **[Holistic deep learning ↗](https://doi.org/10.1007/s10994-023-06482-y)**Dimitris Bertsimas, Kimberly Villalobos Carballo, Léonard Boussioux et al.*11 citations*
63. **[UnbiasedNets: a dataset diversification framework for robustness bias alleviation in neural networks ↗](https://doi.org/10.1007/s10994-023-06314-z)**Mahum Naseer, Bharath Srinivas Prabakaran, Osman Hasan et al.*11 citations*
64. **[Applied machine learning to the determination of biochar hydrogen sulfide adsorption capacity ↗](https://doi.org/10.1007/s10994-023-06446-2)**Abolhassan Banisheikholeslami, Farhad Qaderi*10 citations*
65. **[Automotive fault nowcasting with machine learning and natural language processing ↗](https://doi.org/10.1007/s10994-023-06398-7)**John Pavlopoulos, Alv Romell, Jacob Curman et al.*10 citations*
66. **[Constrained regret minimization for multi-criterion multi-armed bandits ↗](http://dx.doi.org/10.1007/s10994-022-06291-9)**Anmol Kagrecha, Jayakrishnan Nair, Krishna Jagannathan*10 citations*
67. **[Refining neural network predictions using background knowledge ↗](https://doi.org/10.1007/s10994-023-06310-3)**Alessandro Daniele, Emile van Krieken, Luciano Serafini et al.*10 citations*
68. **[Spike2CGR: an efficient method for spike sequence classification using chaos game representation ↗](https://doi.org/10.1007/s10994-023-06371-4)**Taslim Murad, Sarwan Ali, Imdadullah Khan et al.*10 citations*
69. **[Cross-model consensus of explanations and beyond for image classification models: an empirical study ↗](https://doi.org/10.1007/s10994-023-06312-1)**Xuhong Li, Haoyi Xiong, Siyu Huang et al.*9 citations*
70. **[DOC^3: deep one class classification using contradictions ↗](https://doi.org/10.1007/s10994-023-06362-5)**Sauptik Dhar, Bernardo Gonzalez-Torres*9 citations*
71. **[Early anomaly detection in time series: a hierarchical approach for predicting critical health episodes ↗](https://doi.org/10.1007/s10994-022-06300-x)**Vítor Cerqueira, Luı́s Torgo, Carlos Soares*9 citations*
72. **[Fast parameterless prototype-based co-clustering ↗](https://doi.org/10.1007/s10994-023-06474-y)**Elena Battaglia, Federico Peiretti, Ruggero G. Pensa*9 citations*
73. **[Learning domain invariant representations of heterogeneous image data ↗](https://doi.org/10.1007/s10994-023-06374-1)**Mihailo Obrenović, Thomas A. Lampert, Milos R. Ivanovic et al.*9 citations*
74. **[Model-based trajectory stitching for improved behavioural cloning and its applications ↗](https://doi.org/10.1007/s10994-023-06392-z)**Charles A. Hepburn, Giovanni Montana*9 citations*
75. **[Multi-agent reinforcement learning for fast-timescale demand response of residential loads ↗](https://doi.org/10.1007/s10994-023-06460-4)**Vincent Mai, Philippe Maisonneuve, Tianyu Zhang et al.*9 citations*
76. **[Relational data embeddings for feature enrichment with background information ↗](https://doi.org/10.1007/s10994-022-06277-7)**Alexis Cvetkov-Iliev, Alexandre Allauzen, Gael P. Varoquaux*9 citations*
77. **[Understanding Machine Learning ↗](http://dx.doi.org/10.1201/9781003290100-2)**T V Geetha, Selvaraju Sendhilkumar*9 citations*
78. **[A3T: accuracy aware adversarial training ↗](https://doi.org/10.1007/s10994-023-06341-w)**Enes Altınışık, Safa Messaoud, Hüsrev Taha Sencar et al.*8 citations*
79. **[Balancing policy constraint and ensemble size in uncertainty-based offline reinforcement learning ↗](https://doi.org/10.1007/s10994-023-06458-y)**Alex Beeson, Giovanni Montana*8 citations*
80. **[Learning state importance for preference-based reinforcement learning ↗](https://doi.org/10.1007/s10994-022-06295-5)**Guoxi Zhang, Hisashi Kashima*8 citations*
81. **[Learning with constraints ↗](https://doi.org/10.1016/b978-0-32-389859-1.00013-1)**Marco Gori, Alessandro Betti, Stefano Melacci*8 citations*
82. **[Temporal silhouette: validation of stream clustering robust to concept drift ↗](https://doi.org/10.1007/s10994-023-06462-2)**Félix Iglesias, Tanja Zseby*8 citations*
83. **[Decentralized Bayesian learning with Metropolis-adjusted Hamiltonian Monte Carlo ↗](https://doi.org/10.1007/s10994-023-06345-6)**Vyacheslav Kungurtsev, Adam D. Cobb, Tara Javidi et al.*7 citations*
84. **[Dynamic weighted ensemble for diarrhoea incidence predictions ↗](https://doi.org/10.1007/s10994-023-06465-z)**Thanh Duy Do, Thuan Dinh Nguyen, Viet Cuong Ta et al.*7 citations*
85. **[Fair tree classifier using strong demographic parity ↗](https://doi.org/10.1007/s10994-023-06376-z)**António Pereira Barata, Frank W. Takes, H.J. van den Herik et al.*7 citations*
86. **[Imbalanced gradients: a subtle cause of overestimated adversarial robustness ↗](https://doi.org/10.1007/s10994-023-06328-7)**Xingjun Ma, Linxi Jiang, Hanxun Huang et al.*7 citations*
87. **[Improving fraud detection via imbalanced graph structure learning ↗](https://doi.org/10.1007/s10994-023-06464-0)**Lingfei Ren, Ruimin Hu, Yang Liu et al.*7 citations*
88. **[On the Discrepancy between Kleinberg’s Clustering Axioms and k-Means Clustering Algorithm Behavior ↗](https://doi.org/10.1007/s10994-023-06308-x)**Mieczysław A. Kłopotek, Robert Albert Kłopotek*7 citations*
89. **[Predicting potential real-time donations in YouTube live streaming services via continuous-time dynamic graphs ↗](https://doi.org/10.1007/s10994-023-06449-z)**Ruidong Jin, Xin Liu, Tsuyoshi Murata*7 citations*
90. **[Smoclust: synthetic minority oversampling based on stream clustering for evolving data streams ↗](https://doi.org/10.1007/s10994-023-06420-y)**Chun Wai Chiu, Leandro Lei Minku*7 citations*
91. **[State-based episodic memory for multi-agent reinforcement learning ↗](https://doi.org/10.1007/s10994-023-06365-2)**Xiao Ma, Wu-Jun Li*7 citations*
92. **[Trimming stability selection increases variable selection robustness ↗](https://doi.org/10.1007/s10994-023-06384-z)**Tino Werner*7 citations*
93. **[Word embeddings for retrieving tabular data from research publications ↗](https://doi.org/10.1007/s10994-023-06472-0)**Alberto Berenguer, José-Norberto Mazón, David Tomás*7 citations*
94. **[Word embeddings-based transfer learning for boosted relational dependency networks ↗](https://doi.org/10.1007/s10994-023-06404-y)**Thais Luca, Aline Paes, Gerson Zaverucha*7 citations*
95. **[A hybrid ensemble method with negative correlation learning for regression ↗](https://doi.org/10.1007/s10994-023-06364-3)**Yun Fei Bai, Ganglin Tian, Yanfei Kang et al.*6 citations*
96. **[Consensus–relevance kNN and covariate shift mitigation ↗](https://doi.org/10.1007/s10994-023-06378-x)**Konstantinos Kalpakis*6 citations*
97. **[Explanatory machine learning for sequential human teaching ↗](https://doi.org/10.1007/s10994-023-06351-8)**Lun Ai, Johannes Langer, Stephen Muggleton et al.*6 citations*
98. **[Large scale multi-output multi-class classification using Gaussian processes ↗](https://doi.org/10.1007/s10994-022-06289-3)**Chunchao Ma, Mauricio A. Álvarez*6 citations*
99. **[Learning key steps to attack deep reinforcement learning agents ↗](https://doi.org/10.1007/s10994-023-06318-9)**Chien-Min Yu, Ming-Hsin Chen, Hsuan-Tien Lin*6 citations*
100. **[Learning principles ↗](https://doi.org/10.1016/b978-0-32-389859-1.00009-x)**Marco Gori, Alessandro Betti, Stefano Melacci*6 citations*

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