UMONS, membres du staff: Publications de Gillis Nicolas

Publications

Nicolas GILLIS

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Nombre de publications : 149

2024

Périodiques scientifiques/Article

Abdolali, M., Barbarino, G., & Gillis, N. (10 December 2024). Dual Simplex Volume Maximization for Simplex-Structured Matrix Factorization. "SIAM Journal on Imaging Sciences, 17" (4), 2362-2391. doi:10.1137/24M1650600
- 86 Dual Simplex Volume Maximization for Simplex-Structured Matrix Factorization.pdf
Daglayan, H., Vary, S., Absil, O., Christiaens, V., Gillis, N., Jacques, L., Leplat, V., & Absil, P.-A. (13 November 2024). An alternating minimization algorithm with trajectory for direct exoplanet detection. The AMAT algorithm. "Astronomy and Astrophysics, 692", 126. doi:10.1051/0004-6361/202451242
- 88 An Alternating Minimization Algorithm with Trajectory for Direct Exoplanet Detection -- The AMAT Algorithm.pdf
Esposito, F., Atif, S. M., & Gillis, N. (September 2024). Accelerated SVD-based initialization for nonnegative matrix factorization. "Computational and Applied Mathematics, 43" (6). doi:10.1007/s40314-024-02905-1
- 87 Accelerated SVD-based initialization for nonnegative matrix factorization.pdf
Gillis, N., & Van Dooren, P. (12 August 2024). Assigning Stationary Distributions to Sparse Stochastic Matrices. "SIAM Journal on Matrix Analysis and Applications, 45" (4), 2184-2210. doi:10.1137/23M1627328
- 85 Assigning Stationary Distributions to Sparse Stochastic Matrices.pdf
Gillis, N., & Luce, R. (18 July 2024). Checking the Sufficiently Scattered Condition using a Global Non-Convex Optimization Software. "IEEE Signal Processing Letters, 31", 1610-1614. doi:10.1109/LSP.2024.3411521
- 84 Checking the SSC with a MIP solver.pdf
Leplat, V., Le Thi Khanh Hien, Onwunta, A., & Gillis, N. (01 April 2024). Deep Nonnegative Matrix Factorization with Beta Divergences. "Neural Computation, 36" (11), 2365-2402. doi:10.1162/neco_a_01679
- 83 Deep Nonnegative Matrix Factorization with Beta Divergences.pdf
Choudhary, N., Gillis, N., & Sharma, P. (07 February 2024). Characterizing matrices with eigenvalues in an LMI region: A dissipative-Hamiltonian approach. "Linear and Multilinear Algebra, 72" (17), 2984-2999. doi:10.1080/03081087.2024.2304144
- 82 Characterizing matrices with eigenvalues in an LMI region - A dissipative-Hamiltonian approach.pdf

Ouvrages/Ouvrage publié en tant qu’auteur, traducteur, etc.

Gillis, N., & Sharma, P. (2024). "Recent Stability Issues for Linear Dynamical Systems". Springer. doi:10.1007/978-3-031-71326-2_1
- matrixnearness.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Dache, A., Vandaele, A., & Gillis, N. (2024). Orthogonal Symmetric Nonnegative Matrix Tri-Factorization. "IEEE International Workshop on Machine Learning for Signal Processing". doi:10.1109/MLSP58920.2024.10734715
- 40 Orthogonal Symmetric Nonnegative Matrix Tri-Factorization - MLSP 2024.pdf
Lefebvre, J., Vandaele, A., & Gillis, N. (2024). Component-wise Squared Factorization. "IEEE International Workshop on Machine Learning for Signal Processing". doi:10.1109/MLSP58920.2024.10734803
- 39 Component-wise squared Factorization MSLP 2024.pdf
Awari, A. A., Nguyen, H., Wertz, S., Vandaele, A., & Gillis, N. (2024). Coordinate Descent Algorithm for Nonlinear Matrix Decomposition with the ReLU function. "European Signal Processing Conference".
- 38 Coordinate Descent Algorithm for Nonlinear Matrix Decomposition with the ReLU function - EUSIPCO 2024.pdf
Vu thanh, O., & Gillis, N. (2024). Minimum-Volume Nonnegative Matrix Completion. "European Signal Processing Conference".
- 37 Nonnegative Matrix Completion with Minimum Volume - EUSIPCO 2024.pdf

Colloques et congrès scientifiques/Communication publiée sur un site web

Loconte, L., Sladek, A., Mengel, S., Trapp, M., Solin, A., Gillis, N., & Vergari, A. (May 2024). "Subtractive Mixture Models via Squaring: Representation and Learning" [Paper presentation]. International Conference on Learning Representations (ICLR), Vienne, Austria.
- 36 Negative Mixture Models via Squaring - ICLR 2024.pdf

Mémoires et thèses/Thèse de doctorat

Vu thanh, O. (2024). "Low-Rank Matrix Factorizations with Volume-based Constraints and Regularizations" [Doctoral thesis, UMONS - University of Mons]. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/49955
- Low-Rank Matrix Factorizations with Volume-based Constraints and Regularizations.pdf

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2023

Parties d’ouvrages/Contribution à des ouvrages collectifs

Brie, D., Gillis, N., & Moussaoui, S. (2023). Non‐negative Matrix Factorization. In Christian Jutten, Leonardo Tomazeli Duarte, ... Saïd Moussaoui, "Source Separation in Physical‐Chemical Sensing". Hoboken, United States: John Wiley & Sons. doi:10.1002/9781119137252.ch3
- Source_Separation_in_Physical_Chemical_Sensing-NMF.pdf

Périodiques scientifiques/Article

Nadisic, N., Gillis, N., & Kervazo, C. (11 July 2023). Smoothed Separable Nonnegative Matrix Factorization. "Linear Algebra and its Applications, 676", 174-204. doi:10.1016/j.laa.2023.07.013
- 81 Smoothed Separable Nonnegative Matrix Factorization.pdf
Vu thanh, O., Gillis, N., & Lecron, F. (31 May 2023). Bounded Simplex-Structured Matrix Factorization: Algorithms, Identifiability and Applications. "IEEE Transactions on Signal Processing, 71", 2434-2447. doi:10.1109/TSP.2023.3289704
- 80 - Bounded Simplex-Structured Matrix Factorization - Algorithms, Identifiability and Applications.pdf
Hautecoeur, C., De Lathauwer, L., Gillis, N., & Glineur, F. (01 April 2023). Least-squares methods for nonnegative matrix factorization over rational functions. "IEEE Transactions on Signal Processing, 71", 1712-1724. doi:10.1109/TSP.2023.3260560
- 79 Least-squares methods for nonnegative matrix factorization over rational functions.pdf
Leplat, V., Nesterov, Y., Gillis, N., & Glineur, F. (01 March 2023). Conic-Optimization Based Algorithms for Nonnegative Matrix Factorization. "Optimization Methods and Software, 38" (4), 837-859. doi:10.1080/10556788.2023.2189714
- 78 Conic-Optimization Based Algorithms for Nonnegative Matrix Factorization.pdf
Hien, L. T. K., Duy Nhat Phan, & Gillis, N. (02 February 2023). An Inertial Block Majorization Minimization Framework for Nonsmooth Nonconvex Optimization. "Journal of Machine Learning Research, 24" (18), 1-41.
- 77 TITAN - An Inertial Block Majorization Minimization Framework for Nonsmooth Nonconvex Optimization.pdf
Gillis, N., & Rajkó, R. (16 January 2023). Partial Identifiability for Nonnegative Matrix Factorization. "SIAM Journal on Matrix Analysis and Applications, 44" (1), 27-52. doi:10.1137/22M1507553
- 76 Partial Identifiability for Nonnegative Matrix Factorization.pdf
De handschutter, P., & Gillis, N. (2023). A consistent and flexible framework for deep matrix factorizations. "Pattern Recognition", 109102. doi:10.1016/j.patcog.2022.109102
- 74 A consistent and flexible framework for deep matrix factorizations.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Daglayan, H., Vary, S., Leplat, V., Gillis, N., & Absil, P.-A. (2023). Direct Exoplanet Detection Using L1 Norm Low-Rank Approximation. "BNAIC/BeNeLearn conference".
- 33 L1 norm low-rank approximation for exoplanet detection - BENELEARN 2023.pdf
Seraghiti, G., Awari, A. A., Vandaele, A., Porcelli, M., & Gillis, N. (2023). Accelerated Algorithms for Nonlinear Matrix Decomposition with the ReLU function. "IEEE International Workshop on Machine Learning for Signal Processing". doi:10.1109/MLSP55844.2023.10285984
- 34 Accelerated Algorithms for Nonlinear Matrix Decomposition with the ReLU function.pdf
Kolomvakis, C., Vandaele, A., & Gillis, N. (2023). Algorithms for Boolean Matrix Factorization using Integer Programming. "IEEE International Workshop on Machine Learning for Signal Processing". doi:10.1109/MLSP55844.2023.10285969
- 35 Algorithms for Boolean Matrix Factorization using Integer Programming.pdf
Kolomvakis, C., & Gillis, N. (2023). Robust Binary Component Decompositions. "IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings". doi:10.1109/ICASSP49357.2023.10096739
- 30 Robust Binary Component Decompositions.pdf
De handschutter, P., Gillis, N., & Blekic, W. (2023). Deep Symmetric Matrix Factorization. "European Signal Processing Conference".
- 31 Deep Symmetric Matrix Factorization.pdf
Vu thanh, O., & Gillis, N. (2023). Identifiability of Polytopic Matrix Factorization. "European Signal Processing Conference". doi:10.23919/EUSIPCO58844.2023.10290012
- 32 Identifiability of Polytopic Matrix Factorization.pdf
Dache, A., Nicolas Nadisic, Vandaele, A., & Gillis, N. (2023). Exact and Heuristic Methods for Simultaneous Sparse Coding. "European Signal Processing Conference". doi:10.23919/EUSIPCO58844.2023.10289845
- 29 Exact and Heuristic Methods for Simultaneous Sparse Coding.pdf

Colloques et congrès scientifiques/Communication publiée sur un site web

Loconte, L., Stefan Mengel, Gillis, N., & Vergari, A. (04 August 2023). "Negative Mixture Models via Squaring" [Paper presentation]. 6th UAI Workshop on Tractable Probabilistic Modeling, Pittsburgh, United States.
- 36 Negative Mixture Models via Squaring.pdf

Mémoires et thèses/Thèse de doctorat

De handschutter, P. (2023). "Multilayer and deep matrix factorizations" [Doctoral thesis, UMONS - Université de Mons]. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/49814
- PDH_PHD_version_à_imprimer.pdf

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2022

Périodiques scientifiques/Article

Ohib, R., Gillis, N., Dalmasso, N., Shah, S., Potluru, V. K., & Plis, S. (2022). Explicit Group Sparse Projection with Applications to Deep Learning and NMF. "Transactions on Machine Learning Research".
- 75 Explicit Group Sparse Projection with Applications to Deep Learning and NMF.pdf
Nadisic, N., Cohen, J. E., Vandaele, A., & Gillis, N. (10 October 2022). Matrix-wise ℓ0-constrained Sparse Nonnegative Least Squares. "Machine Learning, 111", 4453-4495. doi:10.1007/s10994-022-06260-2
- 72 Matrix-wise L0-constrained Sparse Nonnegative Least Squares.pdf
Abdolali, M., & Gillis, N. (2022). Revisiting data augmentation for subspace clustering. "Knowledge-Based Systems", 109974. doi:10.1016/j.knosys.2022.109974
- 73 Revisiting data augmentation for subspace clustering.pdf
Gillis, N., Le, T. K. H., Leplat, V., & Tan, V. Y. F. (01 August 2022). Distributionally Robust and Multi-Objective Nonnegative Matrix Factorization. "IEEE Transactions on Pattern Analysis and Machine Intelligence, 8", 4052-4064. doi:10.1109/TPAMI.2021.3058693
- 55_Distributionally_Robust_and_Multi-Objective_Nonnegative_Matrix_Factorization.pdf
Hien, L. T. K., Phan, D. N., & GILLIS, N. (19 July 2022). Inertial alternating direction method of multipliers for non-convex non-smooth optimization. "Computational Optimization and Applications, 83", 247-285. doi:10.1007/s10589-022-00394-8
- 71 Inertial Alternating Direction Method of Multipliers for Non-Convex Non-Smooth Optimization.pdf
Baghel, M. K., Gillis, N., & Sharma, P. (07 April 2022). On the non-symmetric semidefinite Procrustes problem. "Linear Algebra and its Applications, 648", 133-159. doi:10.1016/j.laa.2022.04.001
- 70_On_the_non-symmetric_semidefinite_Procrustes_problem.pdf
Leplat, V., Gillis, N., & Févotte, C. (01 April 2022). Multi-Resolution Beta-Divergence NMF for Blind Spectral Unmixing. "Signal Processing, 193".
- 69_Multi-Resolution_Beta-Divergence_NMF_for_Blind_Spectral_Unmixing.pdf
Le, T. K. H., Phan, D. N., Gillis, N., Ahookhosh, M., & Patrinos, P. (13 January 2022). Block Alternating Bregman Majorization Minimization with Extrapolation. "SIAM Journal on Mathematics of Data Science, 4" (1), 1-25.
- 66_Block_Alternating_Bregman_Majorization_Minimization_with_Extrapolation.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Abdolali, M., & Gillis, N. (2022). Subspace Clustering Using Unsupervised Data Augmentation. "IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings". doi:10.1109/ICASSP43922.2022.9746944
- 27_Subspace_Clustering_Using_Unsupervised_Data_Augmentation_-_ICASSP_22.pdf
Vu Thanh, O., Gillis, N., & Lecron, F. (2022). Bounded Simplex-Structured Matrix Factorization. "IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings". doi:10.1109/ICASSP43922.2022.9747124
- 26_Bounded_Simplex_Structured_Matrix_Factorization_-_ICASSP_22.pdf

Colloques et congrès scientifiques/Communication publiée sur un site web

Vu thanh, O., Nadisic, N., & Gillis, N. (05 September 2022). "Randomized Successive Projection Algorithm" [Paper presentation]. Colloque GRETSI.
- 28 Randomized Successive Projection Algorithm.pdf

Mémoires et thèses/Thèse de doctorat

Nadisic, N. (2022). "Sparsity and Nonnegativity in Least Squares Problems and Matrix Factorizations" [Doctoral thesis, UMONS - Université de Mons]. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/49820
- 2022-PhDThesis_NicolasNadisic.pdf

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2021

Périodiques scientifiques/Article

Atif, S. M., Gillis, N., Qazi, S., & Naseem, I. (15 October 2021). Structured Nonnegative Matrix Factorization for Traffic Flow Estimation of Large Cloud Networks. "Computer Networks, 201".
- 68_Structured_Nonnegative_Matrix_Factorization_for_Traffic_Flow_Estimation_of_Large_Cloud_Networks.pdf
Abdolali, M., & Gillis, N. (12 October 2021). Beyond Linear Subspace Clustering: A Comparative Study of Nonlinear Manifold Clustering Algorithms. "Computer Science Review, 42".
- 67_Beyond_Linear_Subspace_Clustering_-_A_Comparative_Study_of_Nonlinear_Manifold_Clustering_Algorithms.pdf
Kervazo, C., Gillis, N., & Dobigeon, N. (10 September 2021). Provably robust blind source separation of linear-quadratic near-separable mixtures. "SIAM Journal on Imaging Sciences, 14" (4), 1848-1889.
- 65_Provably_robust_blind_source_separation_of_linear-quadratic_near-separable_mixtures.pdf
De Handschutter, P., Gillis, N., & Siebert, X. (10 August 2021). A Survey on Deep Matrix Factorizations. "Computer Science Review, 42".
- 64 A survey on deep matrix factorizations.pdf
Gillis, N., & Sharma, P. (01 August 2021). Minimal-norm static feedbacks using dissipative Hamiltonian matrices. "Linear Algebra and its Applications, 623", 258-281. doi:10.1016/j.laa.2020.02.008
- 48_Minimal-norm_static_feedbacks_using_dissipative_Hamiltonian_matrices.pdf
Baghel, M. K., Gillis, N., & Sharma, P. (15 June 2021). Characterization of the dissipative mappings and their application to perturbations of dissipative-Hamiltonian systems. "Numerical Linear Algebra with Applications, 28" (6).
- 63_Characterization_of_the_dissipative_mappings_and_their_application_to_perturbations_of_dissipative-Hamiltonian_systems.pdf
Ahookhosh, M., Le, T. K. H., Gillis, N., & Patrinos, P. (07 June 2021). A block inertial Bregman proximal algorithm for nonsmooth nonconvex problems with application to symmetric nonnegative matrix tri-factorization. "Journal of Optimization Theory and Applications, 190", 234-258.
- 62_A_block_inertial_Bregman_proximal_algorithm_for_nonsmooth_nonconvex_problems_with_application_to_symmetric_nonnegative_matrix_tri-factorization.pdf
Ahookhosh, M., Le, T. K. H., Gillis, N., & Patrinos, P. (28 May 2021). Multi-block Bregman proximal alternating linearized minimization and its application to sparse orthogonal nonnegative matrix factorization. "Computational Optimization and Applications, 79", 681-715.
- 61_Multi-block_Bregman_proximal_alternating_linearized_minimization_and_its_application_to_sparse_orthogonal_nonnegative_matrix_factorization.pdf
Pan, J., & Gillis, N. (01 May 2021). Generalized Separable Nonnegative Matrix Factorization. "IEEE Transactions on Pattern Analysis and Machine Intelligence, 43" (N° spécial), 1546-1561.
- 45_Generalized_Separable_Nonnegative_Matrix_Factorization.pdf
Le, T. K. H., & Gillis, N. (01 May 2021). Algorithms for Nonnegative Matrix Factorization with the Kullback-Leibler Divergence. "Journal of Scientific Computing, 87".
- 60_Algorithms_for_Nonnegative_Matrix_Factorization_with_the_Kullback-Leibler_Divergence.pdf
Ang, M. S., Cohen, J. E., Gillis, N., & Le, T. K. H. (05 March 2021). Accelerating Block Coordinate Descent for Nonnegative Tensor Factorization. "Numerical Linear Algebra with Applications, 28" (5).
- 59_Accelerating_Block_Coordinate_Descent_for_Nonnegative_Tensor_Factorization.pdf
Abdolali, M., & Gillis, N. (19 February 2021). Simplex-Structured Matrix Factorization: Sparsity-based Identifiability and Provably Correct Algorithms. "SIAM Journal on Mathematics of Data Science, 3" (2), 593-623.
- 57_Simplex-Structured_Matrix_Factorization_-_Sparsity-based_Identifiability_and_Provably_Correct_Algorithms.pdf
Leplat, V., Gillis, N., & Idier, J. (18 February 2021). Multiplicative Updates for NMF with β-Divergences under Disjoint Equality Constraints. "SIAM Journal on Matrix Analysis and Applications, 42" (2), 730-752.
- 56_Multiplicative_Updates_for_NMF_with_beta-Divergences_under_Disjoint_Equality_Constraints.pdf
Marrinan, T., Absil, P.-A., & Gillis, N. (01 February 2021). On a minimum enclosing ball of a collection of linear subspaces. "Linear Algebra and its Applications, 625", 248-278.
- 58_On_a_minimum_enclosing_ball_of_a_collection_of_linear_subspaces.pdf
Moutier, F., Vandaele, A., & Gillis, N. (19 January 2021). Off-diagonal symmetric nonnegative matrix factorization. "Numerical Algorithms, 88", 939-963. doi:10.1007/s11075-020-01063-9
- 54_Off-diagonal_symmetric_nonnegative_matrix_factorization.pdf
Dewez, J., Gillis, N., & Glineur, F. (01 January 2021). A geometric lower bound on the extension complexity of polytopes based on the f-vector. "Discrete Applied Mathematics, 303", 22-38. doi:10.1016/j.dam.2020.09.028
- 53_A_geometric_lower_bound_on_the_extension_complexity_of_polytopes_based_on_the_f-vector.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Nadisic, N., Vandaele, A., Gillis, N., & Cohen, J. E. (2021). Exact biobjective k-sparse nonnegative least squares. "European Signal Processing Conference". doi:10.23919/EUSIPCO54536.2021.9616202
- 22_Exact_Biobjective_k-Sparse_Nonnegative_Least_Squares_-_EUSIPCO_2021.pdf
De Handschutter, P., & Gillis, N. (2021). Deep orthogonal matrix factorization as a hierarchical clustering technique. "European Signal Processing Conference". doi:10.23919/EUSIPCO54536.2021.9615998
- 23_Deep_orthogonal_matrix_factorization_as_a_hierarchical_clustering_technique_-_EUSIPCO_2021.pdf
Vu Thanh, O., Ang, M. S., Gillis, N., & Le, T. K. H. (2021). Inertial Majorization-Minimization Algorithm for Minimum-Volume NMF. "European Signal Processing Conference". doi:10.23919/EUSIPCO54536.2021.9616152
- 25_Inertial_Majorization-Minimization_Algorithm_for_Minimum-Volume_NMF_-_EUSIPCO_2021.pdf
Ang, M. S., Leplat, V., & Gillis, N. (2021). Fast algorithm for complex-NMF with application to source separation. "European Signal Processing Conference". doi:10.23919/EUSIPCO54536.2021.9616335
- 24_Fast_algorithm_for_complex-NMF_with_application_to_source_separation_-_EUSIPCO_2021.pdf
Ohib, R., Gillis, N., Shah, S., Potluru, V., & Plis, S. (2021). Grouped Sparse Projection for Deep Learning. "International Conference on Learning Representations".
- 21_Grouped_Sparse_Projection_for_Deep_Learning_-_ICLR-HAET.pdf
Ang, M. S., Gillis, N., Vandaele, A., & De Sterck, H. (2021). Nonnegative Unimodal Matrix Factorization. "IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings". doi:10.1109/ICASSP39728.2021.9414631
- 20_Nonnegative_Unimodal_Matrix_Factorization_-_ICASSP_2021.pdf

Mémoires et thèses/Thèse de doctorat

Coppitters, D. (2021). "Robust design optimization of hybrid renewable energy systems" [Doctoral thesis, Université de Mons]. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/28929
- thesis_coppitters.pdf
Leplat, V. (2021). "Nonnegative Matrix Factorization Models, Optimization Problems, Algorithms and Applications" [Doctoral thesis, UMONS - Université de Mons]. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/49819
- 2021-PhDThesis_ValentinLeplat.pdf

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2020

Périodiques scientifiques/Article

Ghazli, K., Gillis, N., & Moulaï, M. (2020). Optimizing over the properly efficient set of convex multi-objective optimization problems. "Annals of Operations Research". doi:10.1007/s10479-020-03820-4
- 52_Optimizing_over_the_properly_efficient_set_of_convex_multi-objective_optimization_problems.pdf
Fu, X., Vervliet, N., De Lathauwer, L., Huang, K., & Gillis, N. (10 September 2020). Nonconvex Optimization Tools for Large-Scale Matrix and Tensor Decomposition with Structured Factors. "IEEE Signal Processing Magazine, 37" (5), 78-94.
- 51_Computing_Large-Scale_Matrix_and_Tensor_Decomposition_With_Structured_Factors_-_A_Unified_Nonconvex_Optimization_Perspective.pdf
Leplat, V., Gillis, N., & Ang, M. S. (29 April 2020). Blind Audio Source Separation with Minimum-Volume Beta-Divergence NMF. "IEEE Transactions on Signal Processing, 68", 3400-3410.
- 50_Blind_Audio_Source_Separation_with_Minimum-Volume_Beta-Divergence_NMF.pdf
Degleris, A., & Gillis, N. (26 March 2020). A Provably Correct and Robust Algorithm for Convolutive Nonnegative Matrix Factorization. "IEEE Transactions on Signal Processing, 68" (1), 2499-2512.
- 49_A_Provably_Correct_and_Robust_Algorithm_for_Convolutive_Nonnegative_Matrix_Factorization.pdf
De Handschutter, P., Gillis, N., Vandaele, A., & Siebert, X. (01 March 2020). Near-Convex Archetypal Analysis. "IEEE Signal Processing Letters, 27" (1), 81-85.
- 47_Near-Convex_Archetypal_Analysis.pdf
Choudhary, N., Gillis, N., & Sharma, P. (28 February 2020). On approximating the nearest Ω-stable matrix. "Numerical Linear Algebra with Applications, 27" (3).
- 46_On_approximating_the_nearest-stable_matrix.pdf
Gillis, N., Karow, M., & Sharma, P. (01 February 2020). A note on approximating the nearest stable discrete-time descriptor system with fixed rank. "Applied Numerical Mathematics, 148", 131-139.
- 44_A_note_on_approximating_the_nearest_stable_discrete-time_descriptor_systems_with_fixed_rank.pdf

Ouvrages/Ouvrage publié en tant qu’auteur, traducteur, etc.

Gillis, N. (2020). "Nonnegative Matrix Factorization". SIAM Publishing.
- NMFbook_SIAM_reprint.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Nadisic, N., Vandaele, A., Cohen, J. E., & Gillis, N. (2020). Sparse Separable Nonnegative Matrix Factorization. "European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases". doi:10.1007/978-3-030-67658-2_20
- 19_Sparse_Separable_Nonnegative_Matrix_Factorization_-_ECML_2020.pdf
Le, T. K. H., Gillis, N., & Patrinos, P. (2020). Inertial Block Proximal Methods for Non-Convex Non-Smooth Optimization. "International Conference on Machine Learning".
- 18_Inertial_Block_Proximal_Methods_for_Non-Convex_Non-Smooth_Optimization_-_ICML_2020.pdf
Marrinan, T., & Gillis, N. (2020). Hyperspectral Unmixing with Rare Endmembers via Minimax Nonnegative Matrix Factorization. "European Signal Processing Conference". doi:10.23919/Eusipco47968.2020.9287456
- 16_Hyperspectral_Unmixing_with_Rare_Endmembers_via_Minimax_Nonnegative_Matrix_Factorization_-_EUSIPCO_2020.pdf
Kervazo, C., Gillis, N., & Dobigeon, N. (2020). Successive Nonnegative Projection Algorithm for Linear Quadratic Mixtures. "European Signal Processing Conference". doi:10.23919/Eusipco47968.2020.9287788
- 17_Successive_Nonnegative_Projection_Algorithm_for_Linear_Quadratic_Mixtures_-_EUSIPCO_2020.pdf
Nadisic, N., Vandaele, A., Gillis, N., & Cohen, J. E. (2020). Exact Sparse Nonnegative Least Squares. "IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings".
- 13_Exact_Sparse_Nonnegative_Least_Squares.pdf
Ang, M. S., Cohen, J. E., Le, T. K. H., & Gillis, N. (2020). Extrapolated Alternating Algorithms for Approximate Canonical Polyadic Decomposition. "IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings".
- 14_Extrapolated_Alternating_Algorithms_for_Approximate_Canonical_Polyadic_Decomposition.pdf

Mémoires et thèses/Thèse de doctorat

Ang, M. S. (2020). "Nonnegative Matrix and Tensor Factorizations: Models, Algorithms and Applications" [Doctoral thesis, UMONS - Université de Mons]. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/49818
- 2020-PhDThesis_AndersenAng.pdf

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2019

Périodiques scientifiques/Article

Ang, M. S., & Gillis, N. (10 July 2019). Algorithms and Comparisons of Non-negative Matrix Factorization with Volume Regularization for Hyperspectral Unmixing. "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12" (12), 4843-4853.
- 41_Algorithms_and_Comparisons_of_Non-negative_Matrix_Factorization_with_Volume_Regularization_for_Hyperspectral_Unmixing.pdf
Gillis, N., & Shitov, Y. (10 July 2019). Low-Rank Matrix Approximation in the Infinity Norm. "Linear Algebra and its Applications, 581", 367-382.
- 42_Low-Rank_Matrix_Approximation_in_the_Infinity_Norm.pdf
Cohen, J. E., & Gillis, N. (10 July 2019). Identifiability of Complete Dictionary Learning. "SIAM Journal on Mathematics of Data Science, 1" (3), 518-536.
- 43_Identifiability_of_Complete_Dictionary_Learning.pdf
Abdolali, M., Gillis, N., & Rahmati, M. (19 May 2019). Scalable and Robust Sparse Subspace Clustering Using Randomized Clustering and Multilayer Graphs. "Signal Processing, 163", 166-180.
- 40 Scalable and Robust Sparse Subspace Clustering Using Randomized Clustering and Multilayer Graphs.pdf
Esposito, F., Gillis, N., & Del Buono, N. (22 April 2019). Orthogonal joint sparse NMF for microarray data analysis. "Journal of Mathematical Biology, 79" (1), 223-247.
- 39 Orthogonal joint sparse NMF for microarray data analysis.pdf
Gillis, N., Karow, M., & Sharma, P. (26 March 2019). Approximating the nearest stable discrete-time system. "Linear Algebra and its Applications, 573", 37-53.
- 38 Approximating the nearest stable discrete-time system.pdf
Atif, S. M., Qazi, S., & Gillis, N. (18 February 2019). Improved SVD-based Initialization for Nonnegative Matrix Factorization using Low-Rank Correction. "Pattern Recognition Letters, 122", 53-59.
- 37 Improved SVD-based initialization for nonnegative matrix factorization using low-rank correction.pdf
Ang, M. S., & Gillis, N. (18 January 2019). Accelerating Nonnegative Matrix Factorization Algorithms Using Extrapolation. "Neural Computation, 31" (2), 417-439.
- 36 Accelerating Nonnegative Matrix Factorization Algorithms using Extrapolation.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Gillis, N. (2019). Successive Projection Algorithm Robust to Outliers. "IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing".
- 15_Successive_Projection_Algorithm_Robust_to_Outliers_-_CAMSAP_2019.pdf
Ang, M. S., Cohen, J. E., & Gillis, N. (2019). Accelerating Approximate Nonnegative Canonical Polyadic Decomposition using Extrapolation. "GRETSI".
- gretsien_accNNCPD.pdf
Leplat, V., Gillis, N., Siebert, X., & Ang, M. S. (2019). Séparation aveugle de sources sonores par factorization en matrices positives avec pénalité sur le volume du dictionnaire. "GRETSI".
- leplat460-2.pdf
Gillis, N. (2019). Separable Simplex-Structured Matrix Factorization: Robustness of Combinatorial Approaches. "IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings".
- 10 Separable Simplex-Structured Matrix Factorization Robustness of Combinatorial Approaches - ICASSP 19.pdf
Leplat, V., Ang, M. S., & Gillis, N. (2019). Minimum-Volume Rank-Deficient Nonnegative Matrix Factorizations. "IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings".
- 11 Minimum-Volume Rank-Deficient Nonnegative Matrix Factorizations - ICASSP 2019.pdf
Cohen, J. E., & Gillis, N. (2019). Nonnegative Low-Rank Sparse Component Analysis. "IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings".
- 12 Nonnegative Low-Rank Sparse Component Analysis - ICASSP 2019.pdf

Allocutions et communications diverses/Article grand public

Gillis, N. (2019). Learning with Nonnegative Matrix Factorizations. "SIAM News 25 (5)".
- SIAM_NEWS_June2019.pdf

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2018

Périodiques scientifiques/Article

Gillis, N., & Vavasis, S. (13 June 2018). On the Complexity of Robust PCA and ℓ1-Norm Low-Rank Matrix Approximation. "Mathematics of Operations Research, 43" (4), 1072-1084. doi:10.1287/moor.2017.0895
- 27 On the Complexity of Robust PCA and l1-norm low-rank matrix approximation.pdf
Gillis, N., & Sharma, P. (17 April 2018). Finding the nearest positive-real system. "SIAM Journal on Numerical Analysis, 56" (2), 1022-1047.
- 34 Finding the nearest positive-real system.pdf
Gillis, N. (01 April 2018). Multiplicative Updates for Polynomial Root Finding. "Information Processing Letters, 132", 14-18.
- 30 Multiplicative Updates for Polynomial Root Finding.pdf
Cohen, J., & Gillis, N. (01 April 2018). Dictionary-based Tensor Canonical Polyadic Decomposition. "IEEE Transactions on Signal Processing, 66" (7), 1876-1889.
- 29 Dictionary-based Tensor Canonical Polyadic Decomposition.pdf
Vandaele, A., Glineur, F., & Gillis, N. (21 March 2018). Algorithms for positive semidefinite factorization. "Computational Optimization and Applications, 71" (1), 193-219.
- 35 Algorithms for positive semidefinite factorization.pdf
Gillis, N., & Sharma, P. (01 March 2018). A semi-analytical approach for the positive semidefinite Procrustes problem. "Linear Algebra and its Applications, 540", 112-137.
- 31 A semi-analytical approach for the positive semidefinite Procrustes problem.pdf
Cohen, J., & Gillis, N. (01 February 2018). Spectral Unmixing with Multiple Dictionaries. "IEEE Geoscience and Remote Sensing Letters, 15" (2), 187-191.
- 32 Spectral Unmixing with Multiple Dictionaries.pdf
Gillis, N., Mehrmann, V., & Sharma, P. (18 January 2018). Computing nearest stable matrix pairs. "Numerical Linear Algebra with Applications, 25" (5).
- 33 Computing nearest stable matrix pairs.pdf
Sobrie, O., Gillis, N., Mousseau, V., & Pirlot, M. (01 January 2018). UTA-poly and UTA-splines: additive value functions with polynomial marginals. "European Journal of Operational Research, 264", 405-418.
- 25 UTA-poly and UTA-splines - Additive value functions with polynomial marginals.pdf
Gillis, N., & Luce, R. (01 January 2018). A Fast Gradient Method for Nonnegative Sparse Regression with Self Dictionary. "IEEE Transactions on Image Processing, 27" (1), 24-37.
- 28 A Fast Gradient Method for Nonnegative Sparse Regression with Self Dictionary.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Ang, M. S., & Gillis, N. (2018). Volume regularized Non-negative Matrix Factorisations. "Workshop on hyperspectral image and signal processing evolution in remote sensing".
- 20180925conf.pdf

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2017

Périodiques scientifiques/Compte rendu et recension critique d’ouvrage

Gillis, N. (01 March 2017). Introduction to Nonnegative Matrix Factorization. "SIAG/OPT Views and News, 25" (1), 7-16.
- SIAG-OPT - Introduction to NMF.7-16.pdf

Périodiques scientifiques/Article

Gillis, N., & Sharma, P. (01 November 2017). On computing the distance to stability for matrices using linear dissipative Hamiltonian systems. "Automatica, 85", 113-121.
- 26 On computing the distance to stability for matrices using linear dissipative Hamiltonian systems.pdf
Vandaele, A., Gillis, N., & Glineur, F. (15 May 2017). On the Linear Extension Complexity of Regular n-gons. "Linear Algebra and its Applications, 521", 217-239.
- 24 On the Linear Extension Complexity of Regular n-gons.pdf
Belachew, M. T., & Gillis, N. (01 April 2017). Solving the Maximum Clique Problem with Symmetric Rank-One Non-negative Matrix Approximation. "Journal of Optimization Theory and Applications, 173" (1), 279-296.
- 23 Solving the Maximum Clique Problem with Symmetric Rank-One Non-negative Matrix Approximation.pdf
Casalino, G., & Gillis, N. (04 March 2017). Sequential Dimensionality Reduction for Extracting Localized Features. "Pattern Recognition, 63", 15-29.
- 22 Sequential Dimensionality Reduction for Extracting Localized Features.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Cohen, J., & Gillis, N. (2017). A New Approach to Dictionary-Based Nonnegative Matrix Factorization. "European Signal Processing Conference".
- A New Approach to Dictionary-Based NMF.pdf
Cohen, J., Comon, P., & Gillis, N. (2017). Some theory on Non-negative Tucker Decomposition. "LVA/ICA: Latent Variable Analysis and Signal Separation".
- LVAICACohen.pdf

Colloques et congrès scientifiques/Communication poster

Ang, M. S., & Gillis, N. (28 August 2017). "Log-determinant constrained Non-negative Matrix Factorization" [Poster presentation]. Autumn School: Optimization in Machine Learning and Data Science, Trier, Germany.
- 20170827_AutumnSchool_A0_poster.pdf

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2016

Périodiques scientifiques/Article

Vandaele, A., Gillis, N., Lei, Q., Zhong, K., & Dhillon, I. (01 November 2016). Efficient and Non-Convex Coordinate Descent for Symmetric Nonnegative Matrix Factorization. "IEEE Transactions on Signal Processing, 64" (21), 5571-5584.
- 21 Efficient and Non-Convex Coordinate Descent for Symmetric Nonnegative Matrix Factorization.pdf
Vandaele, A., Gillis, N., Glineur, F., & Tuyttens, D. (01 June 2016). Heuristics for exact nonnegative matrix factorization. "Journal of Global Optimization, 65" (2), 369-400.
- 19 Heuristics for exact nonnegative matrix factorization.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Sobrie, O., Gillis, N., Mousseau, V., & Pirlot, M. (2016). "UTA-splines: additive value functions with polynomials" [Paper presentation]. 28th European Conference on Operational Research, Poznan, Poland.
- main.pdf

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2015

Périodiques scientifiques/Compte rendu et recension critique d’ouvrage

Mahmoudi, S., Benjelloun, M., Vankerkem, M., Libert, G., Gillis, N., & Tuyttens, D. (2015). Les projets IG : innovation permanente, réalisations diverses, un travail en équipe et des clients réels. "Polytech News", (52), 20-21.
Larhmam, M., Mahmoudi, S., Benjelloun, M., & Gillis, N. (2015). La vision par ordinateur au service de l'oncologie. "Polytech News", (51), 13.

Périodiques scientifiques/Article

Gillis, N., & Kumar, A. (15 October 2015). Exact and Heuristic Algorithms for Semi-Nonnegative Matrix Factorization. "SIAM Journal on Matrix Analysis and Applications, 36" (4), 1404-1424.
- 20 Exact and Heuristic Algorithms for Semi-Nonnegative Matrix Factorization.pdf
Gillis, N., & Ma, W.-K. (21 May 2015). Enhancing Pure-Pixel Identification Performance via Preconditioning. "SIAM Journal on Imaging Sciences, 8" (2), 1161-1186.
- 18 Enhancing Pure-Pixel Identification Performance via Preconditioning.pdf
Gillis, N., Kuang, D., & Park, H. (01 April 2015). Hierarchical Clustering of Hyperspectral Images using Rank-Two Nonnegative Matrix Factorization. "IEEE Transactions on Geoscience and Remote Sensing, 53" (4), 2066-2078.
- 16 Hierarchical Clustering of Hyperspectral Imagesusing Rank-Two NMF.pdf
Gillis, N., & Vavasis, S. A. (26 March 2015). Semidefinite Programming Based Preconditioning for More Robust Near-Separable Nonnegative Matrix Factorization. "SIAM Journal on Optimization, 25" (1), 677-698.
- 17 Semidefinite Programming Based Preconditioning for More Robust Near-Separable Nonnegative Matrix Factorization.pdf

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2014

Parties d’ouvrages/Contribution à des ouvrages collectifs

Gillis, N. (2014). The Why and How of Nonnegative Matrix Factorization. In "Regularization, Optimization, Kernels, and Support Vector Machines". Chapman Hall / CRC Press.

Périodiques scientifiques/Article

Pompili, F., Gillis, N., Absil, P.-A., & Glineur, F. (02 October 2014). Two Algorithms for Orthogonal Nonnegative Matrix Factorization with Application to Clustering. "Neurocomputing, 141", 15-25.
- 13 Two Algorithms for Orthogonal Nonnegative Matrix Factorization with Application to Clustering.pdf
Gillis, N. (24 June 2014). Successive Nonnegative Projection Algorithm for Robust Nonnegative Blind Source Separation. "SIAM Journal on Imaging Sciences, 7" (2), 1420-1450.
- 15 Successive Nonnegative Projection Algorithm for Robust Nonnegative Blind Source Separation.pdf
Gillis, N., & Luce, R. (01 April 2014). Robust Near-Separable Nonnegative Matrix Factorization Using Linear Optimization. "Journal of Machine Learning Research, 15" (Apr), 1249-1280.
- 14 Robust Near-Separable Nonnegative Matrix Factorization Using Linear Optimization.pdf
Gillis, N., & Vavasis, S. A. (24 March 2014). Fast and Robust Recursive Algorithms for Separable Nonnegative Matrix Factorization. "IEEE Transactions on Pattern Analysis and Machine Intelligence, 36" (4), 698-714. doi:10.1109/TPAMI.2013.226
- 12 Fast and Robust Recursive Algorithms for Separable NMF.pdf
Ma, W.-K., Bioucas-Dias, J. M., Chan, T.-H., Gillis, N., Gader, P., & Plaza, A. (01 January 2014). A Signal Processing Perspective on Hyperspectral Unmixing: Insights from Remote Sensing. "IEEE Signal Processing Magazine, 31" (1), 67-81.
- 11 Signal processing perspective on hyperspectral unmixing.pdf
Gillis, N., & Glineur, F. (01 January 2014). A continuous characterization of the maximum-edge biclique problem. "Journal of Global Optimization, 58" (3), 439-464.
- 09 A continuous characterization of the maximum-edge biclique problem.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Gillis, N. (2014). "Semidefinite Programming Based Preconditioning for More Robust Near-Separable Nonnegative Matrix Factorization" [Paper presentation]. international Traveling Workshop on Interactions between Sparse models and Technology (iTWIST), Namur, Belgium.
Gillis, N. (2014). "Semidefinite Programming Based Preconditioning for More Robust Near-Separable Nonnegative Matrix Factorization" [Paper presentation]. Semidefinite Programming Based Preconditioning for More Robust Near-Separable Nonnegative Matrix Factorization, International Symposium on Mathematical Theory of Networks and Systems (MTNS), Netherlands.
Gillis, N. (2014). "The Why and How of Nonnegative Matrix Factorization" [Paper presentation]. Belgian-Dutch Conference on Machine Learning (BENELEARN), Bruxelles, Belgium.
- benelearn2014_submission_1b.pdf

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2013

Périodiques scientifiques/Article

Gillis, N. (06 August 2013). Robustness Analysis of Hottopixx, a Linear Programming Model for Factoring Nonnegative Matrices. "SIAM Journal on Matrix Analysis and Applications, 34" (3), 1189-1212.
- 10 Robustness Analysis of Hottopixx - a linear programming model for factoring nonnegative matrices.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Pompili, F., Gillis, N., Absil, P.-A., & Glineur, F. (2013). ONP-MF: An Orthogonal Nonnegative Matrix Factorization Algorithm with Application to Clustering. "European Symposium on Artificial Neural Networks".
- 05 ONP-MF An Orthogonal Nonnegative Matrix Factorization Algorithm with Application to Clustering.pdf

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2012

Périodiques scientifiques/Article

Gillis, N. (01 December 2012). Sparse and Unique Nonnegative Matrix Factorization Through Data Preprocessing. "Journal of Machine Learning Research, 13" (2012), 3349-3386.
- 08 Sparse and Unique Nonnegative Matrix Factorization Through Data Preprocessing.pdf
Gillis, N., & Glineur, F. (13 April 2012). On the Geometric Interpretation of the Nonnegative Rank. "Linear Algebra and its Applications, 437" (11), 2685-2712.
- 07 On the Geometric Interpretation of the Nonnegative Rank.pdf
Gillis, N., & Plemmons, R. (09 April 2012). Sparse nonnegative matrix underapproximation and its application to hyperspectral image analysis. "Linear Algebra and its Applications, 438" (10), 3991-4007.
- 06 Sparse NMU and its application to HSI.pdf
Gillis, N., & Glineur, F. (01 January 2012). Accelerated Multiplicative Updates and Hierarchical ALS Algorithms for Nonnegative Matrix Factorization. "Neural Computation, 24" (4), 1085-1105.
- 05 Accelerated MU and HALS Algorithms for NMF.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Gillis, N., Plemmons, R., & Zhang, Q. (2012). Priors in Sparse Recursive Decompositions of Hyperspectral Images. "Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery".
- 04 Priors in Sparse Recursive Decompositions of HSI.pdf

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2011

Périodiques scientifiques/Article

Gillis, N., & Glineur, F. (22 September 2011). A multilevel approach for nonnegative matrix factorization. "Journal of Computational and Applied Mathematics, 236" (7), 1708-1723.
- 04 A Multilevel Approach for Nonnegative Matrix Factorization.pdf
Gillis, N., & Glineur, F. (25 June 2011). Low-Rank Matrix Approximation with Weights or Missing Data is NP-hard. "SIAM Journal on Matrix Analysis and Applications, 32" (4), 1149-1165.
- 03 Low-Rank Matrix Approximtion with Weights or Missing Data is NP-hard.pdf
Gillis, N., & Plemmons, R. (01 February 2011). Dimensionality Reduction, Classification, and Spectral Mixture Analysis using Nonnegative Underapproximation. "Optical Engineering, 50" (2), 027001.
- 02 Dimensionality reduction classification and spectral mixture analysis using non-negative underapproximation.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Gillis, N., & Plemmons, R. (2011). Sparse Nonnegative Matrix Underapproximation and its Application for Hyperspectral Image Analysis. "worskshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing".
- 03 Sparse NMU for HSI.pdf

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2010

Périodiques scientifiques/Article

Gillis, N., & Glineur, F. (01 April 2010). Using underapproximations for sparse nonnegative matrix factorization. "Pattern Recognition, 43" (4), 1676-1687.
- 01 Using underapproximations for sparse nonnegative matrix factorization.pdf

Colloques et congrès scientifiques/Communication publiée dans un périodique

Gillis, N., & Plemmons, R. (2010). Dimensionality Reduction, Classification, and Spectral Mixture Analysis using Nonnegative Underapproximation. "Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery".
- 02 Dimensionality Reduction, Classification, and Spectral Mixture Analysis using NMU.pdf

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2009

Colloques et congrès scientifiques/Communication publiée dans un périodique

Berry, M., Gillis, N., & Glineur, F. (2009). Document Classification Using Nonnegative Matrix Factorization and Underapproximation. "IEEE International Symposium on Circuits and Systems".
- 01 Document classification using NMU.pdf

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