Profil

Gillis Nicolas

Université de Mons - UMONS > Faculté Polytechnique > Service de Mathématique et Recherche opérationnelle

ORCID
0000-0001-6423-6897
Main Referenced Co-authors
Vandaele, Arnaud  (14)
Glineur, François (13)
Ang, Man Shun  (11)
Cohen, Jeremy E. (9)
Le, Thi Khanh Hien  (9)
Main Referenced Keywords
Applied Mathematics (1); Computational Mathematics (1); Control and Optimization (1);
Main Referenced Unit & Research Centers
CRTI - Centre de Recherche en Technologie de l'Information (3)
Main Referenced Disciplines
Mathematics (131)
Computer science (114)
Electrical & electronics engineering (99)
Chemistry (1)
Physics (1)

Publications (total 133)

The most downloaded
392 downloads
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. https://hdl.handle.net/20.500.12907/42427

The most cited

390 citations (Scopus®)

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. https://hdl.handle.net/20.500.12907/41560

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.
Peer reviewed

Leplat, V., Le Thi Khanh Hien, Onwunta, A., & Gillis, N. (2024). Deep Nonnegative Matrix Factorization with Beta Divergences. Neural Computation.
Peer Reviewed verified by ORBi

Choudhary, N., Gillis, N., & Sharma, P. (2024). Characterizing matrices with eigenvalues in an LMI region: A dissipative-Hamiltonian approach. Linear and Multilinear Algebra. doi:10.1080/03081087.2024.2304144
Peer Reviewed verified by ORBi

Daglayan, H., Vary, S., Leplat, V., Gillis, N., & Absil, P.-A. (2023). Direct Exoplanet Detection Using L1 Norm Low-Rank Approximation. BNAIC/BeNeLearn conference.
Peer reviewed

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
Editorial reviewed

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
Peer reviewed

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
Peer reviewed

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.
Peer reviewed

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
Peer Reviewed verified by ORBi

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
Peer reviewed

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
Peer Reviewed verified by ORBi

De handschutter, P., Gillis, N., & Blekic, W. (2023). Deep Symmetric Matrix Factorization. European Signal Processing Conference.
Peer reviewed

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
Peer reviewed

Vu thanh, O., & Gillis, N. (2023). Identifiability of Polytopic Matrix Factorization. European Signal Processing Conference. doi:10.23919/EUSIPCO58844.2023.10290012
Peer reviewed

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
Peer Reviewed verified by ORBi

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
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

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
Peer Reviewed verified by ORBi

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
Peer Reviewed verified by ORBi

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.
Peer reviewed

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
Peer Reviewed verified by ORBi

Abdolali, M., & Gillis, N. (2022). Revisiting data augmentation for subspace clustering. Knowledge-Based Systems, 109974. doi:10.1016/j.knosys.2022.109974
Peer Reviewed verified by ORBi

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

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
Peer Reviewed verified by ORBi

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
Peer Reviewed verified by ORBi

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
Peer reviewed

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
Peer Reviewed verified by ORBi

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
Peer reviewed

Leplat, V., Gillis, N., & Févotte, C. (01 April 2022). Multi-Resolution Beta-Divergence NMF for Blind Spectral Unmixing. Signal Processing, 193.
Peer Reviewed verified by ORBi

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.
Peer reviewed

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.
Peer Reviewed verified by ORBi

Abdolali, M., & Gillis, N. (12 October 2021). Beyond Linear Subspace Clustering: A Comparative Study of Nonlinear Manifold Clustering Algorithms. Computer Science Review, 42.
Peer reviewed

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.
Peer reviewed

De Handschutter, P., Gillis, N., & Siebert, X. (10 August 2021). A Survey on Deep Matrix Factorizations. Computer Science Review, 42.
Peer reviewed

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
Peer Reviewed verified by ORBi

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).
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

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
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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.
Peer Reviewed verified by ORBi

Le, T. K. H., & Gillis, N. (01 May 2021). Algorithms for Nonnegative Matrix Factorization with the Kullback-Leibler Divergence. Journal of Scientific Computing, 87.
Peer Reviewed verified by ORBi

Ohib, R., Gillis, N., Shah, S., Potluru, V., & Plis, S. (2021). Grouped Sparse Projection for Deep Learning. International Conference on Learning Representations.
Peer reviewed

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).
Peer Reviewed verified by ORBi

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.
Peer reviewed

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.
Peer Reviewed verified by ORBi

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
Peer reviewed

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.
Peer Reviewed verified by ORBi

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
Peer Reviewed verified by ORBi

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
Peer Reviewed verified by ORBi

Gillis, N. (2020). Nonnegative Matrix Factorization. SIAM Publishing.

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
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

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
Peer reviewed

Le, T. K. H., Gillis, N., & Patrinos, P. (2020). Inertial Block Proximal Methods for Non-Convex Non-Smooth Optimization. International Conference on Machine Learning.
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

De Handschutter, P., Gillis, N., Vandaele, A., & Siebert, X. (01 March 2020). Near-Convex Archetypal Analysis. IEEE Signal Processing Letters, 27 (1), 81-85.
Peer Reviewed verified by ORBi

Choudhary, N., Gillis, N., & Sharma, P. (28 February 2020). On approximating the nearest Ω-stable matrix. Numerical Linear Algebra with Applications, 27 (3).
Peer Reviewed verified by ORBi

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.
Peer reviewed

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.
Peer reviewed

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.
Peer Reviewed verified by ORBi

Gillis, N. (2019). Successive Projection Algorithm Robust to Outliers. IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing.
Peer reviewed

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.
Peer reviewed

Ang, M. S., Cohen, J. E., & Gillis, N. (2019). Accelerating Approximate Nonnegative Canonical Polyadic Decomposition using Extrapolation. GRETSI.
Peer reviewed

Cohen, J. E., & Gillis, N. (10 July 2019). Identifiability of Complete Dictionary Learning. SIAM Journal on Mathematics of Data Science, 1 (3), 518-536.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

Gillis, N., & Shitov, Y. (10 July 2019). Low-Rank Matrix Approximation in the Infinity Norm. Linear Algebra and its Applications, 581, 367-382.
Peer Reviewed verified by ORBi

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

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.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

Gillis, N., Karow, M., & Sharma, P. (26 March 2019). Approximating the nearest stable discrete-time system. Linear Algebra and its Applications, 573, 37-53.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

Cohen, J. E., & Gillis, N. (2019). Nonnegative Low-Rank Sparse Component Analysis. IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings.
Peer reviewed

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.
Peer reviewed

Gillis, N. (2019). Separable Simplex-Structured Matrix Factorization: Robustness of Combinatorial Approaches. IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings.
Peer reviewed

Ang, M. S., & Gillis, N. (18 January 2019). Accelerating Nonnegative Matrix Factorization Algorithms Using Extrapolation. Neural Computation, 31 (2), 417-439.
Peer Reviewed verified by ORBi

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

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.
Peer Reviewed verified by ORBi

Gillis, N., & Sharma, P. (17 April 2018). Finding the nearest positive-real system. SIAM Journal on Numerical Analysis, 56 (2), 1022-1047.
Peer Reviewed verified by ORBi

Cohen, J., & Gillis, N. (01 April 2018). Dictionary-based Tensor Canonical Polyadic Decomposition. IEEE Transactions on Signal Processing, 66 (7), 1876-1889.
Peer Reviewed verified by ORBi

Gillis, N. (01 April 2018). Multiplicative Updates for Polynomial Root Finding. Information Processing Letters, 132, 14-18.
Peer Reviewed verified by ORBi

Vandaele, A., Glineur, F., & Gillis, N. (21 March 2018). Algorithms for positive semidefinite factorization. Computational Optimization and Applications, 71 (1), 193-219.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

Cohen, J., & Gillis, N. (01 February 2018). Spectral Unmixing with Multiple Dictionaries. IEEE Geoscience and Remote Sensing Letters, 15 (2), 187-191.
Peer Reviewed verified by ORBi

Gillis, N., Mehrmann, V., & Sharma, P. (18 January 2018). Computing nearest stable matrix pairs. Numerical Linear Algebra with Applications, 25 (5).
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

Gillis, N., & Sharma, P. (01 November 2017). On computing the distance to stability for matrices using linear dissipative Hamiltonian systems. Automatica, 85, 113-121.
Peer Reviewed verified by ORBi

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.

Cohen, J., & Gillis, N. (2017). A New Approach to Dictionary-Based Nonnegative Matrix Factorization. European Signal Processing Conference.
Peer reviewed

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.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

Casalino, G., & Gillis, N. (04 March 2017). Sequential Dimensionality Reduction for Extracting Localized Features. Pattern Recognition, 63, 15-29.
Peer Reviewed verified by ORBi

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

Cohen, J., Comon, P., & Gillis, N. (2017). Some theory on Non-negative Tucker Decomposition. LVA/ICA: Latent Variable Analysis and Signal Separation.
Peer reviewed

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.
Peer Reviewed verified by ORBi

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.

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.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

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.

Gillis, N., & Ma, W.-K. (21 May 2015). Enhancing Pure-Pixel Identification Performance via Preconditioning. SIAM Journal on Imaging Sciences, 8 (2), 1161-1186.
Peer reviewed

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.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

Larhmam, M., Mahmoudi, S., Benjelloun, M., & Gillis, N. (2015). La vision par ordinateur au service de l'oncologie. Polytech News, (51), 13.

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

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.
Peer Reviewed verified by ORBi

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. (24 June 2014). Successive Nonnegative Projection Algorithm for Robust Nonnegative Blind Source Separation. SIAM Journal on Imaging Sciences, 7 (2), 1420-1450.
Peer reviewed

Gillis, N. (2014). The Why and How of Nonnegative Matrix Factorization [Paper presentation]. Belgian-Dutch Conference on Machine Learning (BENELEARN), Bruxelles, Belgium.

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.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

Gillis, N., & Glineur, F. (01 January 2014). A continuous characterization of the maximum-edge biclique problem. Journal of Global Optimization, 58 (3), 439-464.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

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.
Peer reviewed

Gillis, N. (01 December 2012). Sparse and Unique Nonnegative Matrix Factorization Through Data Preprocessing. Journal of Machine Learning Research, 13 (2012), 3349-3386.
Peer Reviewed verified by ORBi

Gillis, N., & Glineur, F. (13 April 2012). On the Geometric Interpretation of the Nonnegative Rank. Linear Algebra and its Applications, 437 (11), 2685-2712.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

Gillis, N., & Glineur, F. (01 January 2012). Accelerated Multiplicative Updates and Hierarchical ALS Algorithms for Nonnegative Matrix Factorization. Neural Computation, 24 (4), 1085-1105.
Peer Reviewed verified by ORBi

Gillis, N., Plemmons, R., & Zhang, Q. (2012). Priors in Sparse Recursive Decompositions of Hyperspectral Images. Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery.
Peer reviewed

Gillis, N., & Glineur, F. (22 September 2011). A multilevel approach for nonnegative matrix factorization. Journal of Computational and Applied Mathematics, 236 (7), 1708-1723.
Peer Reviewed verified by ORBi

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.
Peer Reviewed verified by ORBi

Gillis, N., & Plemmons, R. (01 February 2011). Dimensionality Reduction, Classification, and Spectral Mixture Analysis using Nonnegative Underapproximation. Optical Engineering: the Journal of the Society of Photo-Optical Instrumentation Engineers, 50 (2), 027001.
Peer Reviewed verified by ORBi

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.
Peer reviewed

Gillis, N., & Glineur, F. (01 April 2010). Using underapproximations for sparse nonnegative matrix factorization. Pattern Recognition, 43 (4), 1676-1687.
Peer Reviewed verified by ORBi

Gillis, N., & Plemmons, R. (2010). Dimensionality Reduction, Classification, and Spectral Mixture Analysis using Nonnegative Underapproximation. Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery.
Peer reviewed

Berry, M., Gillis, N., & Glineur, F. (2009). Document Classification Using Nonnegative Matrix Factorization and Underapproximation. IEEE International Symposium on Circuits and Systems.
Peer reviewed

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