Olivier Caelen

Publication Activity (10 Years)

Years Active: 2005-2023
Publications (10 Years): 29

Top Topics

Fraud Detection

Categorical Variables

Machine Learning

Top Venues

Int. J. Data Sci. Anal.

Future Gener. Comput. Syst.

Publications

Daniele Lunghi, Gian Marco Paldino, Olivier Caelen, Gianluca Bontempi
An Adversary Model of Fraudsters' Behavior to Improve Oversampling in Credit Card Fraud Detection. IEEE Access 11 (2023)
Danele Lunghi, Alkis Simitsis, Olivier Caelen, Gianluca Bontempi
Adversarial Learning in Real-World Fraud Detection: Challenges and Perspectives. CoRR (2023)
Daniele Lunghi, Alkis Simitsis, Olivier Caelen, Gianluca Bontempi
Adversarial Learning in Real-World Fraud Detection: Challenges and Perspectives. DEC@SIGMOD (2023)
Fabrizio Carcillo, Yann-Aël Le Borgne, Olivier Caelen, Yacine Kessaci, Frédéric Oblé, Gianluca Bontempi
Combining unsupervised and supervised learning in credit card fraud detection. Inf. Sci. 557 (2021)
Gabriele Gianini, Leopold Ghemmogne Fossi, Corrado Mio, Olivier Caelen, Lionel Brunie, Ernesto Damiani
Managing a pool of rules for credit card fraud detection by a Game Theory based approach. Future Gener. Comput. Syst. 102 (2020)
Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Liyun He-Guelton, Olivier Caelen, Michael Granitzer, Sylvie Calabretto
Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs. Future Gener. Comput. Syst. 102 (2020)
Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Sylvie Calabretto, Olivier Caelen, Liyun He-Guelton, Michael Granitzer
Multiple perspectives HMM-based feature engineering for credit card fraud detection. SAC (2019)
Jacopo De Stefani, Yann-Aël Le Borgne, Olivier Caelen, Dalila Hattab, Gianluca Bontempi
Batch and incremental dynamic factor machine learning for multivariate and multi-step-ahead forecasting. Int. J. Data Sci. Anal. 7 (4) (2019)
Théo Verhelst, Olivier Caelen, Jean-Christophe Dewitte, Bertrand Lebichot, Gianluca Bontempi
Understanding Telecom Customer Churn with Machine Learning: From Prediction to Causal Inference. BNAIC/BENELEARN (Selected Papers) (2019)
Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Liyun He-Guelton, Olivier Caelen, Michael Granitzer, Sylvie Calabretto
Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs. CoRR (2019)
Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Olivier Caelen, Liyun He-Guelton, Sylvie Calabretto, Michael Granitzer
Multiple perspectives HMM-based feature engineering for credit card fraud detection. CoRR (2019)
Théo Verhelst, Olivier Caelen, Jean-Christophe Dewitte, Bertrand Lebichot, Gianluca Bontempi
Understanding Telecom Customer Churn with Machine Learning: From Prediction to Causal Inference. BNAIC/BENELEARN (2019)
Johannes Jurgovsky, Michael Granitzer, Konstantin Ziegler, Sylvie Calabretto, Pierre-Edouard Portier, Liyun He-Guelton, Olivier Caelen
Sequence classification for credit-card fraud detection. Expert Syst. Appl. 100 (2018)
Fabrizio Carcillo, Yann-Aël Le Borgne, Olivier Caelen, Gianluca Bontempi
Correction to: Streaming active learning strategies for real-life credit detection: assessment and visualization. Int. J. Data Sci. Anal. 5 (4) (2018)
Fabrizio Carcillo, Yann-Aël Le Borgne, Olivier Caelen, Gianluca Bontempi
Streaming Active Learning Strategies for Real-Life Credit Card Fraud Detection: Assessment and Visualization. CoRR (2018)
Jacopo De Stefani, Olivier Caelen, Dalila Hattab, Yann-Aël Le Borgne, Gianluca Bontempi
A Multivariate and Multi-step Ahead Machine Learning Approach to Traditional and Cryptocurrencies Volatility Forecasting. MIDAS/PAP@PKDD/ECML (2018)
Fabrizio Carcillo, Andrea Dal Pozzolo, Yann-Aël Le Borgne, Olivier Caelen, Yannis Mazzer, Gianluca Bontempi
SCARFF: A scalable framework for streaming credit card fraud detection with spark. Inf. Fusion 41 (2018)
Andrea Dal Pozzolo, Giacomo Boracchi, Olivier Caelen, Cesare Alippi, Gianluca Bontempi
Credit Card Fraud Detection: A Realistic Modeling and a Novel Learning Strategy. IEEE Trans. Neural Networks Learn. Syst. 29 (8) (2018)
Fabrizio Carcillo, Yann-Aël Le Borgne, Olivier Caelen, Gianluca Bontempi
Streaming active learning strategies for real-life credit card fraud detection: assessment and visualization. Int. J. Data Sci. Anal. 5 (4) (2018)
Jordan Fréry, Amaury Habrard, Marc Sebban, Olivier Caelen, Liyun He-Guelton
Online Non-linear Gradient Boosting in Multi-latent Spaces. IDA (2018)
Yoan Russac, Olivier Caelen, Liyun He-Guelton
Embeddings of Categorical Variables for Sequential Data in Fraud Context. AMLTA (2018)
Konstantin Ziegler, Olivier Caelen, Mathieu Garchery, Michael Granitzer, Liyun He-Guelton, Johannes Jurgovsky, Pierre-Edouard Portier, Stefan Zwicklbauer
Injecting Semantic Background Knowledge into Neural Networks using Graph Embeddings. WETICE (2017)
Fabrizio Carcillo, Andrea Dal Pozzolo, Yann-Aël Le Borgne, Olivier Caelen, Yannis Mazzer, Gianluca Bontempi
SCARFF: a Scalable Framework for Streaming Credit Card Fraud Detection with Spark. CoRR (2017)
Olivier Caelen
A Bayesian interpretation of the confusion matrix. Ann. Math. Artif. Intell. 81 (3-4) (2017)
Fabrizio Carcillo, Yann-Aël Le Borgne, Olivier Caelen, Gianluca Bontempi
An Assessment of Streaming Active Learning Strategies for Real-Life Credit Card Fraud Detection. DSAA (2017)
Jordan Fréry, Amaury Habrard, Marc Sebban, Olivier Caelen, Liyun He-Guelton
Efficient Top Rank Optimization with Gradient Boosting for Supervised Anomaly Detection. ECML/PKDD (1) (2017)
Jacopo De Stefani, Olivier Caelen, Dalila Hattab, Gianluca Bontempi
Machine Learning for Multi-step Ahead Forecasting of Volatility Proxies. MIDAS@PKDD/ECML (2017)
Fabian Braun, Olivier Caelen, Evgueni N. Smirnov, Steven Kelk, Bertrand Lebichot
Improving Card Fraud Detection Through Suspicious Pattern Discovery. IEA/AIE (2) (2017)
Bertrand Lebichot, Fabian Braun, Olivier Caelen, Marco Saerens
A graph-based, semi-supervised, credit card fraud detection system. COMPLEX NETWORKS (2016)
Andrea Dal Pozzolo, Giacomo Boracchi, Olivier Caelen, Cesare Alippi, Gianluca Bontempi
Credit card fraud detection and concept-drift adaptation with delayed supervised information. IJCNN (2015)
Véronique Van Vlasselaer, Cristián Bravo, Olivier Caelen, Tina Eliassi-Rad, Leman Akoglu, Monique Snoeck, Bart Baesens
APATE: A novel approach for automated credit card transaction fraud detection using network-based extensions. Decis. Support Syst. 75 (2015)
Andrea Dal Pozzolo, Olivier Caelen, Reid A. Johnson, Gianluca Bontempi
Calibrating Probability with Undersampling for Unbalanced Classification. SSCI (2015)
Andrea Dal Pozzolo, Olivier Caelen, Gianluca Bontempi
When is Undersampling Effective in Unbalanced Classification Tasks? ECML/PKDD (1) (2015)
Andrea Dal Pozzolo, Olivier Caelen, Yann-Aël Le Borgne, Serge Waterschoot, Gianluca Bontempi
Learned lessons in credit card fraud detection from a practitioner perspective. Expert Syst. Appl. 41 (10) (2014)
Andrea Dal Pozzolo, Reid A. Johnson, Olivier Caelen, Serge Waterschoot, Nitesh V. Chawla, Gianluca Bontempi
Using HDDT to avoid instances propagation in unbalanced and evolving data streams. IJCNN (2014)
Andrea Dal Pozzolo, Olivier Caelen, Serge Waterschoot, Gianluca Bontempi
Racing for Unbalanced Methods Selection. IDEAL (2013)
Gianluca Bontempi, Olivier Caelen
A Selecting-the-Best Method for Budgeted Model Selection. ECML/PKDD (1) (2011)
Olivier Caelen, Gianluca Bontempi
A dynamic programming strategy to balance exploration and exploitation in the bandit problem. Ann. Math. Artif. Intell. 60 (1-2) (2010)
Olivier Caelen, Gianluca Bontempi, Luc Barvais
Machine Learning Techniques for Decision Support in Anesthesia. AIME (2007)
Olivier Caelen, Gianluca Bontempi
Improving the Exploration Strategy in Bandit Algorithms. LION (2007)
Olivier Caelen, Gianluca Bontempi, Eddy Coussaert, Luc Barvais, Francois Clement
Machine Learning Techniques to Enable Closed-Loop Control in Anesthesia. CBMS (2006)
Patrick Emmanuel Meyer, Olivier Caelen, Gianluca Bontempi
Speeding up Feature Selection by Using an Information Theoretic Bound. BNAIC (2005)
Olivier Caelen, Gianluca Bontempi
How to allocate a restricted budget of leave-one-out assessments for effective model selection in machine learning: a comparison of state-of-the-art techniques. BNAIC (2005)