Sandra Mitrović
Title
Cited by
Cited by
Year
Machine-learned Identification of RR Lyrae Stars from Sparse, Multi-band Data: The PS1 Sample
B Sesar, N Hernitschek, S Mitrović, Ž Ivezić, HW Rix, JG Cohen, ...
The Astronomical Journal 153 (5), 204, 2017
732017
On the operational efficiency of different feature types for telco Churn prediction
S Mitrović, B Baesens, W Lemahieu, J De Weerdt
European Journal of Operational Research 267 (3), 1141-1155, 2018
142018
Combining temporal aspects of dynamic networks with Node2Vec for a more efficient dynamic link prediction
S De Winter, T Decuypere, S Mitrović, B Baesens, J De Weerdt
2018 IEEE/ACM International Conference on Advances in Social Networks …, 2018
82018
Scalable RFM-enriched representation learning for churn prediction
S Mitrovic, G Singh, B Baesens, W Lemahieu, J De Weerdt
2017 IEEE International Conference on Data Science and Advanced Analytics …, 2017
62017
Churn prediction using dynamic rfm-augmented node2vec
S Mitrović, B Baesens, W Lemahieu, J De Weerdt
International Workshop on Personal Analytics and Privacy, 122-138, 2017
62017
Summarizing citation contexts of scientific publications
S Mitrović, H Müller
International Conference of the Cross-Language Evaluation Forum for European …, 2015
62015
tcc2vec: RFM-informed representation learning on call graphs for churn prediction
S Mitrović, B Baesens, W Lemahieu, J De Weerdt
Information Sciences, 2019
52019
Churn modeling with probabilistic meta paths-based representation learning
S Mitrović, J De Weerdt
Information Processing & Management 57 (2), 102052, 2020
22020
Representation learning in graphs for credit card fraud detection
R Van Belle, S Mitrović, J De Weerdt
Workshop on Mining Data for Financial Applications, 32-46, 2019
12019
A comparative study of community detection techniques for large evolving graphs
L Coppens, J De Venter, S Mitrović, J De Weerdt
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019
12019
Dyn2Vec: Exploiting dynamic behaviour using difference networks-based node embeddings for classification
S Mitrovic, J De Weerdt
12018
Predicting branch visits and credit card up-selling using temporal banking data
S Mitrović, G Singh
arXiv preprint arXiv:1607.06123, 2016
12016
A Comparative Study of Representation Learning Techniques for Dynamic Networks
CO Vázquez, S Mitrović, J De Weerdt, S vanden Broucke
World Conference on Information Systems and Technologies, 523-530, 2020
2020
Network Representation Learning for Credit Card Fraud Detection
R Van Belle, S Mitrovic, J De Weerdt, B Baesens
Network Science Society Conference (NETSCI), Date: 2020/09/17-2020/09/25 …, 2020
2020
A comparison of methods for link sign prediction with signed network embeddings
S Mitrović, L Lecoutere, J De Weerdt
Proceedings of the 2019 IEEE/ACM International Conference on Advances in …, 2019
2019
Graph Representation Learning for Fraud Prediction: A Nearest Neighbour Approach
R Van Belle, S Mitrovic, J De Weerdt
https://grlearning. github. io/papers/, 2019
2019
On Feature Engineering and Network Representation Learning for Telco Churn Prediction
S Mitrović
2019
Churn Prediction using representation learning with guided random walks.
S Mitrovic
Joint International Workshop on Social Influence Analysis and Mining …, 2019
2019
Benefits of Using Symmetric Loss in Recommender Systems
G Singh, S Mitrović
European Conference on Information Retrieval, 345-356, 2018
2018
Churn Prediction in Telco using Adapted node2vec on RFM-enriched CDR graphs.
S Mitrovic, B Baesens, W Lemahieu, J De Weerdt
Third Conference on Business Analytics in Finance and Industry (BAFI),, 2018
2018
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Articles 1–20