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 |
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 |
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 |
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 |
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 |
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 |
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 |
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 |