 | 2009 |
|---|
| 8 |       | Etienne Côme,
Latifa Oukhellou,
Thierry Denoeux,
Patrice Aknin:
Noiseless Independent Factor Analysis with Mixing Constraints in a Semi-supervised Framework. Application to Railway Device Fault Diagnosis.
ICANN (2) 2009: 416-425 |
| 7 | | Etienne Côme,
Latifa Oukhellou,
Thierry Denoeux,
Patrice Aknin:
Learning from partially supervised data using mixture models and belief functions.
Pattern Recognition 42(3): 334-348 (2009) |
| 2008 |
|---|
| 6 | | Etienne Côme,
Zohra Leila Cherfi,
Latifa Oukhellou,
Patrice Aknin:
Semi-supervised IFA with Prior Knowledge on the Mixing Process: An Application to a Railway Device Diagnosis.
ICMLA 2008: 415-420 |
| 5 | | Etienne Côme,
Latifa Oukhellou,
Thierry Denoeux,
Patrice Aknin:
Mixture Model Estimation with Soft Labels.
SMPS 2008: 165-174 |
| 2007 |
|---|
| 4 | | Allou Samé,
Latifa Oukhellou,
Etienne Côme,
Patrice Aknin:
Mixture-model-based signal denoising.
Adv. Data Analysis and Classification 1(1): 39-51 (2007) |
| 2004 |
|---|
| 3 | | Alexandra Debiolles,
Latifa Oukhellou,
Patrice Aknin:
Combined Use of Partial Least Squares Regression and Neural Network for Diagnosis Tasks.
ICPR (4) 2004: 573-576 |
| 2001 |
|---|
| 2 | | Françoise Fessant,
Patrice Aknin,
Latifa Oukhellou,
Sophie Midenet:
Comparison of Supervised Self-Organizing Maps Using Euclidian or Mahalanobis Distance in Classification Context.
IWANN (1) 2001: 637-644 |
| 1999 |
|---|
| 1 | | Latifa Oukhellou,
Patrice Aknin:
Hybrid training of radial basis function networks in a partitioning context of classification.
Neurocomputing 28(1-3): 165-175 (1999) |
