Alexandre Aussem


Professeur des universités


Team(s)DM2L
Institution
Université Claude Bernard Lyon 1
Location
Nautibus (Université Lyon1)
Emailalexandre.aussem at liris.cnrs.fr
Professional phone number
Personal page

Publications

Publications LIRIS pour Alexandre Aussem (24)

  • 2019 (1)
  • 2018 (1)
    • Journals (1)
      • International journals with peer review (1)
        •  Denis Lecoeuche, Alex Aussem & Maxime Gasse (2018). "On the use of binary stochastic autoencoders for multi-label classification under the zero-one loss". Procedia Computer Science, vol. 144, pp. 71-80. HAL : hal-02042711.
  • 2017 (2)
    • Conferences (2)
      • International conferences with peer review (2)
        •  Anil Narassiguin, Haytham Elghazel & Alex Aussem (2017). "Dynamic Ensemble Selection with Probabilistic Classifier Chains". European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), 18 septembre 2017, Skopje (Republic of Macedonia), pp. 169-186. HAL : hal-02018695.
        •  Van-Tinh Tran & Alex Aussem (2017). "Reducing variance due to importance weighting in covariate shift bias correction". European Symposium on Artificial Neural Networks, Bruges (Belgium). HAL : hal-02042795.
  • 2016 (7)
    • Journals (3)
      • International journals with peer review (3)
        •  Haytham Elghazel, Alex Aussem, Ouadie Gharroudi & Wafa Saadaoui (2016). "Ensemble Multi-label Text Categorization based on Rotation Forest and Latent Semantic Indexing". Expert Systems with Applications, vol. 57, pp. 1-11. HAL : hal-01375162.
        •  Florence Magrangeas, Rowan Kuiper, Hervé Avet-Loiseau, Wilfried Gouraud, Catherine Guérin-Charbonnel, Ludovic Ferrer, Alexandre Aussem, Haytham Elghazel, Jérôme Suhard et al. (2016). "A Genome-Wide Association Study Identifies a Novel Locus for Bortezomib-Induced Peripheral Neuropathy in European Multiple Myeloma Patients". Clinical Cancer Research, Epub ahead of print. doi : 10.1158/1078-0432.CCR-15-3163. HAL : inserm-01313506. .
        •  Anil Narassiguin, Mohamed Bibimoune, Haytham Elghazel & Alex Aussem (2016). "An Extensive Empirical Comparison of Ensemble Learning Methods for Binary Classification". Pattern Analysis and Applications, vol. 19, #4, pp. 1093-1128. doi : 10.1007/s10044-016-0553-z. HAL : hal-01375159.
    • Conferences (4)
      • International conferences with peer review (4)
        •  Maxime Gasse & Alex Aussem (2016). "F-Measure Maximization in Multi-Label Classification with Conditionally Independent Label Subsets". European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 23 septembre 2016, Riva del garda (Italy), pp. 619-631. doi : 10.1007/978-3-319-46128-1_39. HAL : hal-01425528. .
        •  Maxime Gasse & Alex Aussem (2016). "Identifying the irreducible disjoint factors of a multivariate probability distribution.". Probabilistic Graphical Models, 9 septembre 2016, Lugano (Switzerland), pp. 183-194. HAL : hal-01425447. .
        •  Ouadie Gharroudi, Haytham Elghazel & Alex Aussem (2016). "A Semi-Supervised Ensemble Approach for Multi-label Learning". 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), 15 décembre 2016, Barcelona (Spain), pp. 1197-1204. HAL : hal-02018699.
        •  Anil Narassiguin, Haytham Elghazel & Alex Aussem (2016). "Similarity Tree Pruning: A Novel Dynamic Ensemble Selection Approach". 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), 15 décembre 2016, Barcelona (Spain), pp. 1243-1250. HAL : hal-02018696.
  • 2015 (7)
    • Journals (2)
    • Conferences (5)
      • International conferences with peer review (5)
        •  Van-Tinh Tran & Alex Aussem (2015). "A Practical Approach to Reduce the Learning Bias Under Covariate Shift". ECML PKDD 2015 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 11 septembre 2015, Porto (Portugal), pp 71-86. doi : 10.1007/978-3-319-23525-7_5. HAL : hal-01213965. .
        •  Maxime Gasse, Alex Aussem & Haytham Elghazel (2015). "On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property". International Conference on Machine Learning, 11 juillet 2015, Lille (France), pp. 2531-2539. HAL : hal-01234346. .
        •  Ouadie Gharroudi, Haytham Elghazel & Alex Aussem (2015). "Calibrated k-labelsets for Ensemble Multi-Label Classification". International Conference on Neural Information Processing, 12 novembre 2015, Istanbul (Turkey), pp. 573-582. HAL : hal-01375166.
        •  Ouadie Gharroudi, Haytham Elghazel & Alex Aussem (2015). "Ensemble Multi-label Classification: A Comparative Study on Threshold Selection and Voting Methods". IEEE International Conference on Tools with Artificial Intelligence,, 11 novembre 2015, Vietri sul Mare (Italy), pp. 377-384. HAL : hal-01375164.
        •  Van-Tinh Tran & Alex Aussem (2015). "Correcting a Class of Complete Selection Bias with External Data Based on Importance Weight Estimation". 22nd International Conference, ICONIP 2015, 12 novembre 2015, Istanbul (Turkey). doi : 10.1007/978-3-319-26555-1_13. HAL : hal-01247394. .
  • 2014 (3)
    • Journals (1)
    • Conferences (2)
      • International conferences with peer review (2)
        •  Alex Aussem, Pascal Caillet, Sarah Klemm, Maxime Gasse, Anne-Marie Schott & Michel Ducher (2014). "Analysis of risk factors of hip fracture with causal Bayesian networks". International Work-Conference on Bioinformatics and Biomedical Engineering, 7 avril 2014, Grenade (Spain), pp. 1074-1085. HAL : hal-01326485.
        •  Ouadie Gharroudi, Haytham Elghazel & Alex Aussem (2014). "A Comparison of Multi-Label Feature Selection Methods Using the Random Forest Paradigm". Canadian Conference on Artificial Intelligence, AI, 6 mai 2014, Montréal (Canada), pp. 95-106. HAL : hal-01301070.
  • 2013 (1)
    • Conferences (1)
      • International conferences with peer review (1)
        •  Mohamed Bibimoune, Haytham Elghazel & Alex Aussem (2013). "An Empirical Comparison of Supervised Ensemble Learning Approaches". International Workshop on Complex Machine Learning Problems with Ensemble Methods COPEM@ECML/PKDD'13, 27 septembre 2013, Prague (Czech Republic), pp. 123-138. HAL : hal-01339258.
  • 2012 (2)