Research
Journal articles
Nadisic, N., Gillis, N., & Kervazo, C. (2023). Smoothed separable nonnegative matrix factorization. Linear Algebra and its Applications, 676, 174-204.
[HAL]Kervazo, C., Gillis, N., & Dobigeon, N. (2021). Provably robust blind source separation of linear-quadratic near-separable mixtures. SIAM Journal on Imaging Sciences, 14(4), 1848-1889.
[arXiv] [Matlab] [slides] [video]Kervazo C., Liaudat T., Bobin J. (2020), Faster and Better Sparse Blind Source Separation Through Mini-Batch Optimization. Accepted at Digital Signal Processing.
[HAL] [slides]
Kervazo C., Bobin J., Chenot C. Sureau F. (2020), Use of PALM for l1 Sparse Matrix Factorization: Difficulty and Rationalization of an Heuristic Approach. Digital Signal Processing, 97, 102611.
[DSP] [slides] [poster]Kervazo C., Bobin J., Chenot C. (2018), Blind separation of a large number of sparse sources. Signal Processing, 150, 157-165.
[Signal Processing] [Python] [poster] [slides]
Conference proceedings
Kervazo C., Chetoui A., Cohen J., Deep unrolling of the multiplicative updates algorithm for blind source separation, with application to hyperspectral unmixing. Accepted in EUSIPCO 2024.
Hadjeres R., Kervazo C., Tupin F., Generating synthetic data to train a deep unrolled network for Hyperspectral Unmixing. Accepted in EUSIPCO 2024.
Bultingaire T., Meraoumia I., Kervazo C., Denis L., Tupin F., Unsupervised radiometric change detection from synthetic aperture radar images. Accepted in EUSIPCO 2024.
Dereure E., Kervazo C., Seguin J., Garofalakis A., Mignet N., Angelini E., Olivo-Marin J.C., Wavelet-based sparse non-negative matrix factorization for bioluminescent imaging unmixing. In 21st International Symposium on Biomedical Imaging (ISBI 2024).
Quillent, A., Bismuth, V., Bloch, I., Ladjal, S., & Kervazo, C. (2024, May). Deep-learning uncertainty estimation for data-consistent breast tomosynthesis reconstruction. In 21st International Symposium on Biomedical Imaging (ISBI 2024).
Quillent, A., Bismuth, V., Bloch, I., Kervazo, C., & Ladjal, S. (2023, July). A deep learning method trained on synthetic data for digital breast tomosynthesis reconstruction. In Medical Imaging with Deep Learning 2023 (MIDL 2023).
Dereure, E., Kervazo, C., Seguin, J., Garofalakis, A., Mignet, N., Angelini, E., & Olivo-Marin, J. C. (2023, April). Sparse Non-Negative Matrix Factorization for Preclinical Bioluminescent Imaging. In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI) (pp. 1-5). IEEE.
Kervazo, C., & Ladjal, S. (2022). Extraction des positions continues des cibles dans les signaux RSO. GRETSI conference.
Fahes, M., Kervazo, C., Bobin, J., & Tupin, F. (2021, October). Unrolling PALM for Sparse Semi-Blind Source Separation. In International Conference on Learning Representations.
Kervazo C., Gillis N., Dobigeon N., Successive Nonnegative Projection Algorithm for Linear Quadratic Mixtures, EUSIPCO 2020.
Kervazo C., Gillis N., Dobigeon N., Successive Nonnegative Projection Algorithm for Linear Quadratic Mixtures, iTWISTKervazo C., Bobin J., Block-GMCA. Actes de Conf ́erence de Spars2017.
Kervazo C., Bobin J., Stacked Sparse Non-Linear Blind Source Separation. Spars2019.
Liaudat T., Bobin J., Kervazo C., Distributed Sparse BSS for Large-Scale Datasets. Spars2019.
[Proceeding] [poster]Kervazo C., Bobin J., Chenot C., Heuristics For Efficient Sparse Blind Source Separation. EUSIPCO 2018.
Kervazo C., Bobin J., Chenot C., Heuristics For Efficient Sparse Blind Source Separation. iTWIST 2018.
PhD thesis and thesis of former students
Kervazo C. (2019), Optimization framework for large-scale sparse blind source separation.
[Thesis]