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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Foundations of Machine Learning
Vishal Goar, Nagendra Singh Yadav
Advances in business information systems and analytics book series (2024), pp. 25-48
Closed Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

The digitization of agricultural industry – a systematic literature review on agriculture 4.0
Rabiya Abbasi, Pablo Martı́nez, Rafiq Ahmad
Smart Agricultural Technology (2022) Vol. 2, pp. 100042-100042
Open Access | Times Cited: 311
Unsupervised Learning Based On Artificial Neural Network: A Review
Happiness Ugochi Dike, Yimin Zhou, Kranthi Kumar Deveerasetty, et al.
2018 IEEE International Conference on Cyborg and Bionic Systems (CBS) (2018), pp. 322-327
Closed Access | Times Cited: 154
Early History of Machine Learning
Аlexander L. Fradkov
IFAC-PapersOnLine (2020) Vol. 53, Iss. 2, pp. 1385-1390
Open Access | Times Cited: 126
Distributionally Robust Graph-based Recommendation System
Bohao Wang, Jiawei Chen, Changdong Li, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 3777-3788
Open Access | Times Cited: 9
Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis
Sihao Ding, Peng Wu, Fuli Feng, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2022), pp. 305-315
Closed Access | Times Cited: 28
A Generic Learning Framework for Sequential Recommendation with Distribution Shifts
Zhengyi Yang, Xiangnan He, Jizhi Zhang, et al.
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2023), pp. 331-340
Closed Access | Times Cited: 20
A Survey on Representation Learning Efforts in Cybersecurity Domain
Muhammad Usman, Mian Ahmad Jan, Xiangjian He, et al.
ACM Computing Surveys (2019) Vol. 52, Iss. 6, pp. 1-28
Closed Access | Times Cited: 36
On the Expressibility and Overfitting of Quantum Circuit Learning
Chih-Chieh Chen, Masaya Watabe, Kodai Shiba, et al.
ACM Transactions on Quantum Computing (2021) Vol. 2, Iss. 2, pp. 1-24
Open Access | Times Cited: 30
Towards Unbiased and Accurate Deferral to Multiple Experts
Vijay Keswani, Matthew Lease, Krishnaram Kenthapadi
(2021), pp. 154-165
Open Access | Times Cited: 28
On-Device Learning for Model Personalization with Large-Scale Cloud-Coordinated Domain Adaption
Yikai Yan, Chaoyue Niu, Renjie Gu, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2022), pp. 2180-2190
Closed Access | Times Cited: 16
CDR: Conservative Doubly Robust Learning for Debiased Recommendation
Zijie Song, Jiawei Chen, Sheng Zhou, et al.
(2023), pp. 2321-2330
Open Access | Times Cited: 9
Debiased Recommendation with Noisy Feedback
H. Li, Chunyuan Zheng, Wenjie Wang, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 1576-1586
Open Access | Times Cited: 3
InFi
Mu Yuan, Lan Zhang, Fengxiang He, et al.
Proceedings of the 28th Annual International Conference on Mobile Computing And Networking (2022), pp. 228-241
Closed Access | Times Cited: 15
Enhancing AutoML Performance for Imbalanced Tabular Data Classification: A Self-Balancing Pipeline
Marcelo Vinícius Cysneiros Aragão, Mateus de Freitas Carvalho, Tiago de Morais Pereira, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 2
Incremental learning for matrix factorization in recommender systems
Tong Yu, Ole J. Mengshoel, Alvin Jude, et al.
2021 IEEE International Conference on Big Data (Big Data) (2016), pp. 1056-1063
Closed Access | Times Cited: 18
A Simple but Effective Approach for Unsupervised Few-Shot Graph Classification
Yonghao Liu, Lan Huang, Bowen Cao, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 4249-4259
Closed Access | Times Cited: 1
Boosting Fair Classifier Generalization through Adaptive Priority Reweighing
Zhihao Hu, Yiran Xu, Mengnan Du, et al.
ACM Transactions on Knowledge Discovery from Data (2024)
Open Access | Times Cited: 1
Machine Learning Applied To Fall Detection in the Elderly
Catarina Alves de Oliveira, Cristiano da Silveira Colombo, Daniel José Ventorim Nunes
(2024), pp. 1-9
Closed Access | Times Cited: 1
Noisy Label Removal for Partial Multi-Label Learning
Fuchao Yang, Yuheng Jia, Hui Liu, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 3724-3735
Open Access | Times Cited: 1
Where to Sell
Hamid Nazerzadeh, Renato Paes Leme, Afshin Rostamizadeh, et al.
(2016)
Closed Access | Times Cited: 5
Confidence Ranking for CTR Prediction
Jian Zhu, Congcong Liu, Pei Wang, et al.
(2023), pp. 437-441
Open Access | Times Cited: 2
Penerapan Text Mining Pada Sistem Penyeleksian Judul Skripsi Menggunakan Algoritma Latent Dirichlet Allocation(LDA)
Rakhmat Kurniawan, Ilka Zufria
Indonesian Journal of Computer Science (2022) Vol. 11, Iss. 3
Open Access | Times Cited: 4
Geodesic Forests
Meghana Madhyastha, Gongkai Li, Veronika Strnadová-Neeley, et al.
(2020), pp. 513-523
Open Access | Times Cited: 5
Using Machine Learning on Testing IoT Applications: a systematic mapping
Lavínia Matoso Freitas, Valéria Lelli
(2022), pp. 348-358
Closed Access | Times Cited: 3
Scalable linear classifiers based on exponential loss function
Sandhya Tripathi, N. Hemachandra
(2018), pp. 190-200
Closed Access | Times Cited: 3
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