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Conference Paper
Desmedt C, Loi SM, Haibe-Kains B, Soree A, Lallemand F, Durbecq V, Larsimont D, Tutt A, Ellis P, Gillett C, et al. Four genes by RT-PCR predicts distant relapse for women given adjuvant tamoxifen. In: Breast Cancer Research and Treatment. Vol. 94. Breast Cancer Research and Treatment. ; 2005. p. S129.
Kontos K, André B, van Helden J, Bontempi G. Gaussian Graphical Models to Infer Putative Genes Involved in Nitrogen Catabolite Repression in \textitS. cerevisiae. In: Pizzuti C, Ritchie MD, Giacobini M Proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics (EvoBIO 2009). Vol. 5483. Proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics (EvoBIO 2009). ; 2009. p. 13-24.
Samatopoulos B, Equeter C, Haibe-Kains B, Soree A, Sotiriou C, Bron D, Martiat P, Lagneaux L. Gene expression comparison between B cells expressing high and low level of Zap-70 mRNA reveals distinct profiles, potential therapeutic targets and new prognostic factors for Chronic Lymphocytic Leukemia.
Stamatopoulos B, Haibe-Kains B, Meuleman N, Bron D, Martiat P, Lagneaux L. Gene expression profiles based on ZAP70 mRNA level.
Desmedt C, Azambuja E, Di Leo A, Larsimont D, Durbecq V, Antoine D, Lallemand F, Haibe-Kains B, Cardoso F, Nogaret JM, et al. Gene expression profiling can predict pathological complete response (pCR) to anthracycline-monotherapy in estrogen-receptor (ER) negative breast cancer (BC) patients.
Sotiriou C, Wirapati P, Loi S, Harris A, Bergh J, Smeds J, Farmer P, Praz V, Haibe-Kains B, Lallemand F, et al. Gene Expression Profiling in Breast Cancer Challenges the Existence of Intermediate Histological Grade.
Sotiriou C, Wirapati P, Loi S, Haibe-Kains B, Piette F, Buyse M, Bontempi G, Delorenzi M, Piccart M. Is genomic grading killing histological grading ?. In: Journal of European Breast Cancer. Vol. 4. Journal of European Breast Cancer. ; 2006. p. 177.
Caelen O, Bontempi G. 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.
Leon O, Cuéllar MP, Delgado M, Le Borgne Y, G. B. Human Activity Recognition Framework in monitored environments.
Olsen C, Meyer PE, Bontempi G. On the impact of entropy estimator in transcriptional regulatory network inference.
Kontos K, Bontempi G. An Improved Shrinkage Estimator to Infer Regulatory Networks with Gaussian Graphical Models.
Lerman L, Jr. JN, Veshchikov N. Improving Block Cipher Design by Rearranging Internal Operations. In: Samarati P SECRYPT 2013. SECRYPT 2013. ; 2013. p. 27-38.
Caelen O, Bontempi G. Improving the exploration strategy in bandit algorithms. In: in Science LNC Proceedings of Learning and Intelligent OptimizatioN LION II. Proceedings of Learning and Intelligent OptimizatioN LION II. ; 2007. p. 56-68.
Han TA, Pereira LM. Intention-based Decision Making for Strategic Scenarios Dynamics via Computational Logic.
Lerman L, Markowitch O, Jr. NJ. Key Management as a Service.
Han TA, Pereira LM, Lenaerts T, Santos FC. Learning to recognize intentions resolves cooperation dilemmas.
Abughalieh N, Le Borgne Y, Nowé A, Steenhaut K. Lifetime Optimization for Sensor Networks with Correlated Data Gathering. In: Altman E, Basar T, Chlamtac I Proceedings of the 7th IEEE Conference on Networked Sensing Systems. Proceedings of the 7th IEEE Conference on Networked Sensing Systems. ; 2010. p. 252 – 258.
Le Borgne Y, Van Der Haegen M, Bontempi G. Localization for Wireless Sensor Networks with CC2420 Radios. In: Proceedings of the 7th international conference on new technologies of distributed systems. Vol. 1. Proceedings of the 7th international conference on new technologies of distributed systems. ; 2007. p. 23-28.
Bontempi G. Long Term Time Series Prediction with Multi-Input Multi-Output Local Learning.
Lerman L, Medeiros SF, Bontempi G, Markowitch O. A Machine Learning Approach Against a Masked AES. In: Francillon A, Rohatgi P Smart Card Research and Advanced Applications. Vol. 8419. Smart Card Research and Advanced Applications. ; 2014. p. 61–75.
Lerman L, Medeiros SF, Bontempi G, Markowitch O. A Machine Learning Approach Against a Masked AES. In: Francillon A, Rohatgi P CARDIS 2013. CARDIS 2013. ; 2013. p. 62–77.
Caelen O, Bontempi G, Barvais L. Machine learning techniques for decision support tool in anesthesia.
Caelen O, Bontempi G, Coussaert E, Barvais L, Clement F. Machine Learning Techniques to Enable Closed-Loop Control in Anesthesia.
Kontos K, Godard P, André B, van Helden J, Bontempi G. Machine learning techniques to identify putative genes involved in nitrogen catabolite repression in the yeast \textitSaccharomyces cerevisiae.
Van Sint Jan S, Bontempi G, Summeren VS. Making the links between Rehabilitation and Musculoskeletal modelling: requirements and tools.

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