Article de journal
Stoye, J., Mataigne, S., Absil, P.-A., & Zimmermann, R. (2026). Shortest geodesic loops, sectional curvature, and injectivity radius of the Stiefel manifold. BIT Numerical Mathematics, 66(3), 1-43. https://doi.org/10.1007/s10543-026-01141-9 (Original work published 2026)
Olikier, G., Mlinarić, P., Absil, P.-A., & Uschmajew, A. (2026). The Tangent Cone to the Real Determinantal Variety: Various Expressions and a Proof. Set-Valued and Variational Analysis : theory and applications, 34(8). https://doi.org/10.1007/s11228-026-00796-4 (Original work published 2026)
Olikier, G., Gallivan, K., & Absil, P.-A. (2026). Low-Rank Optimization Methods Based on Projected Projected-Gradient Descent That Accumulate at Bouligand Stationary Points. Mathematics of Operations Research. Published. https://doi.org/10.1287/moor.2024.0582 (Original work published 2026)
Papier de conférence
Mil-Homens Cavaco, N., Jacques, L., & Absil, P.-A. (2025). Exoplanet detection in angular and spectral differential imaging with an accelerated proximal gradient algorithm. ESANN Proceedings. Published. ESANN 2025, Bruges (Belgium) and online. https://doi.org/10.14428/esann/2025.es2025-103 (Original work published 2025)
Mataigne, S., Absil, P.-A., & Miolane, N. (2025). On the Approximation of the Riemannian Barycenter. Lecture Notes in Computer Science : Geometric Science of Information, p. 12-21. https://doi.org/10.1007/978-3-032-03921-7_2
Goyens, F., Absil, P.-A., & Feppon, F. (2025). Geometric Design of the Tangent Term in Landing Algorithms for Orthogonality Constraints. Lecture Notes in Computer Science : Geometric Science of Information, p. 133-141. https://doi.org/10.1007/978-3-032-03924-8_14
Article de journal
Absil, P.-A., & Mataigne, S. (2025). The Ultimate Upper Bound on the Injectivity Radius of the Stiefel Manifold. SIAM Journal on Matrix Analysis and Applications, 46(2), 1145-1167. https://doi.org/10.1137/24m1644808 (Original work published 2025)
Mataigne, S., Absil, P.-A., & Miolane, N. (2025). Bounds on the geodesic distances on the Stiefel manifold for a family of Riemannian metrics. Linear Algebra and Its Applications, 730, 1-34. https://doi.org/10.1016/j.laa.2025.10.003 (Original work published 2026)
Article de journal
Si, W., Absil, P.-A., Huang, W., Jiang, R., & Vary, S. (2024). A Riemannian Proximal Newton Method. SIAM Journal on Optimization, 34(1), 654-681. https://doi.org/10.1137/23m1565097 (Original work published 2023)
Ablin, P., Vary, S., Gao, B., & Absil, P.-A. (2024). Infeasible Deterministic, Stochastic, and Variance-Reduction Algorithms for Optimization under Orthogonality Constraints. Journal of Machine Learning Research, 25(389), 1-38. https://doi.org/10.48550/arXiv.2303.16510 (Original work published 2023)
Bendokat, T., Zimmermann, R., & Absil, P.-A. (2024). A Grassmann manifold handbook: basic geometry and computational aspects. Advances in Computational Mathematics, 50(1). https://doi.org/10.1007/s10444-023-10090-8 (Original work published 2024)
Absil, P.-A., Cojuhari, I., Fiodorov, I., & Tits, A. L. (2024). Strong versions of impulsive controllability and sampled observability. Automatica, 169, 111865. https://doi.org/10.1016/j.automatica.2024.111865 (Original work published 2024)
Daglayan Sevim, H., Vary, S., Absil, O., Cantalloube, F., Christiaens, V., Gillis, N., Jacques, L., Leplat, V., & Absil, P.-A. (2024). An alternating minimization algorithm with trajectory for direct exoplanet detection : The AMAT algorithm. Astronomy & Astrophysics, 692, A126. https://doi.org/10.1051/0004-6361/202451242 (Original work published 2024)
Papier de conférence
Loucheur, B., Absil, P.-A., & Journée, M. (2024). Weather Data Imputation Using Graph-Based Low-Rank Matrix Completion with Variable Projection. Proceedings of BNAIC/BeNeLearn 2024, p. 1-16.
Article de journal
Olikier, G., & Absil, P.-A. (2023). An Apocalypse-Free First-Order Low-Rank Optimization Algorithm with at Most One Rank Reduction Attempt per Iteration. SIAM Journal on Matrix Analysis and Applications, 44(3), 1421-1435. https://doi.org/10.1137/22m1518256 (Original work published 2023)
Vermeylen, C., Olikier, G., Absil, P.-A., & Van Barel, M. (2023). Rank Estimation for Third-Order Tensor Completion in the Tensor-Train Format. Proceedings of the 31st European Signal Processing Conference (EUSIPCO 2023, 965-969. https://doi.org/10.48550/arXiv.2309.15170 (Original work published 2023)
Papier de conférence
Daglayan Sevim, H., Vary, S., Cantalloube, F., Absil, P.-A., & Absil, O. (2023). Likelihood ratio map for direct exoplanet detection. 2022 IEEE 5th International Conference on Image Processing Applications and Systems (IPAS), p. 1-5. https://doi.org/10.1109/ipas55744.2022.10052997
Loucheur, B., Absil, P.-A., & Journée, M. (2023). Graph-Based Matrix Completion Applied to Weather Data. Proceedings of the 31st European Signal Processing Conference (EUSIPCO 2023), 1973-1977. https://doi.org/10.48550/arXiv.2306.08627 (Original work published 2023)
Vary, S., Daglayan Sevim, H., Jacques, L., & Absil, P.-A. (2023). Low-Rank Plus Sparse Trajectory Decomposition for Direct Exoplanet Imaging. “Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on”, 1(1). https://doi.org/10.1109/icassp49357.2023.10096197 (Original work published 2023)
Daglayan Sevim, H., Vary, S., Leplat, V., Gillis, N., & Absil, P.-A. (2023). Direct Exoplanet Detection Using L1 Norm Low-Rank Approximation. Proceedings of BNAIC/BeNeLearn 2023, 1-13. https://doi.org/10.48550/arXiv.2304.03619 (Original work published 2023)
Daglayan Sevim, H., Vary, S., & Absil, P.-A. (2023). An Alternating Minimization Algorithm with Trajectory for Direct Exoplanet Detection. ESANN 2023 proceedings. Published. ESANN 2023 - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges (Belgium) and online. https://doi.org/10.14428/esann/2023.es2023-137
Article de journal
Olikier, G., & Absil, P.-A. (2022). On the Continuity of the Tangent Cone to the Determinantal Variety. Set-Valued and Variational Analysis : theory and applications, 30, 769-788. https://doi.org/10.1007/s11228-022-00629-0 (Original work published 2022)
Berger, G., Absil, P.-A., De Lathauwer, L., Jungers, R., & Van Barel, M. (2022). Equivalent polyadic decompositions of matrix multiplication tensors. Journal of Computational and Applied Mathematics, 406(113941), 1-17. https://doi.org/10.1016/j.cam.2021.113941 (Original work published 2022)
de Borman, A., Vespa, S., El Tahry, R., & Absil, P.-A. (2022). Estimation of seizure onset zone from ictal scalp EEG using independent component analysis in extratemporal lobe epilepsy. Journal of Neural Engineering, 19(2), 026005 [1-14]. https://doi.org/10.1088/1741-2552/ac55ad (Original work published 2022)
Van Hoorebeeck, L., Absil, P.-A., & Papavasiliou, A. (2022). Solving non-convex economic dispatch with valve-point effects and losses with guaranteed accuracy. International Journal of Electrical Power & Energy Systems, 134, 107143. https://doi.org/10.1016/j.ijepes.2021.107143 (Original work published 2022)
Papier de conférence
Gao, B., Vary, S., Ablin, P., & Absil, P.-A. (2022). Optimization flows landing on the Stiefel manifold. IFAC-PapersOnLine, 55(30), 25-30. https://doi.org/10.1016/j.ifacol.2022.11.023 (Original work published 2022)
Article de journal
Nguyen, T. S., Absil, P.-A., Gao, B., & Stykel, T. (2021). Symplectic eigenvalue problem via trace minimization and Riemannian optimization. SIAM Journal on Matrix Analysis and Applications, 42(4), 1732-1757. https://doi.org/10.1137/21m1390621 (Original work published 2021)
Marrinan, T., Absil, P.-A., & Gillis, N. (2021). On a minimum enclosing ball of a collection of linear subspaces. Linear Algebra and Its Applications, 625, 248-278. https://doi.org/10.1016/j.laa.2021.05.006 (Original work published 2021)
Dong, S., Absil, P.-A., & Gallivan, K. A. (2021). Riemannian gradient descent methods for graph-regularized matrix completion. Linear Algebra and Its Applications, 623, 193-235. https://doi.org/10.1016/j.laa.2020.06.010 (Original work published 2021)
Gao, B., Nguyen, T. S., Absil, P.-A., & Stykel, T. (2021). Riemannian Optimization on the Symplectic Stiefel Manifold. SIAM Journal on Optimization, 31(2), 1546-1575. https://doi.org/10.1137/20m1348522 (Original work published 2021)
Gao, B., & Absil, P.-A. (2021). A Riemannian rank-adaptive method for low-rank matrix completion. Computational Optimization and Applications : an international journal. Published. https://doi.org/10.1007/s10589-021-00328-w (Original work published 2021)
Musolas, A., Massart, E., Hendrickx, J., Absil, P.-A., & Marzouk, Y. (2021). Low-rank multi-parametric covariance identification. Bit (Lisse) : numerical mathematics, 62, 221-249. https://doi.org/10.1007/s10543-021-00867-y (Original work published 2021)
Papier de conférence
Gao, B., Nguyen, T. S., Absil, P.-A., & Stykel, T. (2021). Geometry of the Symplectic Stiefel Manifold Endowed with the Euclidean Metric. In Frank Nielsen, Frédéric Barbaresco (Eds.) (ed.), Lecture Notes in Computer Science : Geometric Science of Information (p. p. 789-796). Springer International Publishing,2021. https://doi.org/10.1007/978-3-030-80209-7_85
Article de journal
Massart, E., & Absil, P.-A. (2020). Quotient Geometry with Simple Geodesics for the Manifold of Fixed-Rank Positive-Semidefinite Matrices. SIAM Journal on Matrix Analysis and Applications, 41(1), 171-198. https://doi.org/10.1137/18m1231389 (Original work published 2020)
Yuan, X., Huang, W., Absil, P.-A., & Gallivan, K. A. (2020). Computing the matrix geometric mean: Riemannian versus Euclidean conditioning, implementation techniques, and a Riemannian BFGS method. Numerical Linear Algebra with Applications, 27(5), 2321. https://doi.org/10.1002/nla.2321 (Original work published 2020)
Van Hoorebeeck, L., Absil, P.-A., & Papavasiliou, A. (2020). Global Solution of Economic Dispatch with Valve Point Effects and Transmission Constraints. Electric Power Systems Research, 189, 106786. https://doi.org/10.1016/j.epsr.2020.106786 (Original work published 2020)
Berger, G., Absil, P.-A., Jungers, R., & Nesterov, Y. (2020). On the quality of first-order approximation of functions with Hölder continuous gradient. Journal of Optimization Theory and Applications, 185, 17-33. https://doi.org/10.1007/s10957-020-01632-x (Original work published 2020)
Chapitre de livre
Yuan, X., Huang, W., Absil, P.-A., & Gallivan, K. A. (2019). Averaging Symmetric Positive-Definite Matrices. In Grohs, Philipp ; Holler, Martin ; Weinmann, Andreas (ed.), Hanbook of Variational Methods for Nonlinear Geometric Data and applications (p. p. 555-575). Springer handbooks. https://doi.org/10.1007/978-3-030-31351-7_20
Absil, P.-A., & Hosseini, S. (2019). A Collection of Nonsmooth Riemannian Optimization Problems. In Seyedehsomayeh Hosseini, Boris S. Mordukhovich, André Uschmajew (Eds.) (ed.), International Series of Numerical Mathematics (p. p. 1-15). Springer Nature. https://doi.org/10.1007/978-3-030-11370-4_1
Papier de conférence
Nguyen, T. S., Gousenbourger, P.-Y., Massart, E., & Absil, P.-A. (2019). Online balanced truncation for linear time-varying systems using continuously differentiable interpolation on Grassmann manifold. 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT), p. 165-170. https://doi.org/10.1109/codit.2019.8820675
Massart, E., Hendrickx, J., & Absil, P.-A. (2019). Curvature of the Manifold of Fixed-Rank Positive-Semidefinite Matrices Endowed with the Bures–Wasserstein Metric. Lecture Notes in Computer Science : Geometric Science of Information, p. 739-748. https://doi.org/10.1007/978-3-030-26980-7_77
Massart, E., Gousenbourger, P.-Y., Nguyen, T. S., Stykel, T., & Absil, P.-A. (2019). Interpolation on the manifold of fixed-rank positive-semidefinite matrices for parametric model order reduction: preliminary results. ESANN 2019 Proceedings, p. 281-286.
Renard, E., Absil, P.-A., & Gallivan, K. A. (2019). Minimax center to extract a common subspace from multiple datasets. ESANN 2019 Proceedings, p. 275-280.
Dong, S., Absil, P.-A., & Gallivan, K. A. (2019). Preconditioned conjugate gradient algorithms for graph regularized matrix completion. ESANN 2019 Proceedings, p. 239-244.
Van Hoorebeeck, L., Absil, P.-A., & Papavasiliou, A. (2019). MILP-Based Algorithm for the Global Solution of Dynamic Economic Dispatch Problems with Valve-Point Effects. 2019 IEEE Power & Energy Society General Meeting (PESGM). Published. 2019 IEEE Power & Energy Society General Meeting (PESGM), Atlanta, GA, USA. https://doi.org/10.1109/pesgm40551.2019.8973631
Article de journal
Boumal, N., Absil, P.-A., & Cartis, C. (2018). Global rates of convergence for nonconvex optimization on manifolds. IMA Journal of Numerical Analysis, 39(1), 1-33. https://doi.org/10.1093/imanum/drx080 (Original work published 2018)
Huang, W., Absil, P.-A., Gallivan, K., & Hand, P. (2018). ROPTLIB: an object-oriented C++ library for optimization on Riemannian manifolds. ACM Transactions on Mathematical Software, 44(4). https://doi.org/10.1145/3218822 (Original work published 2018)
Huang, W., Absil, P.-A., & Gallivan, K. A. (2018). A Riemannian BFGS Method Without Differentiated Retraction for Nonconvex Optimization Problems. SIAM Journal on Optimization, 28(1), 470-495. https://doi.org/10.1137/17m1127582 (Original work published 2018)
Gousenbourger, P.-Y., Massart, E., & Absil, P.-A. (2018). Data Fitting on Manifolds with Composite Bézier-Like Curves and Blended Cubic Splines. Journal of Mathematical Imaging and Vision, 61(5), 645-671. https://doi.org/10.1007/s10851-018-0865-2 (Original work published 2018)
Papier de conférence
Renard, E., Gallivan, K. A., & Absil, P.-A. (2018). A Grassmannian Minimum Enclosing Ball Approach for Common Subspace Extraction. Latent Variable Analysis and Signal Separation : Lecture Notes in Computer Science, p. 69-78. https://doi.org/10.1007/978-3-319-93764-9_7
Dong, S., Absil, P.-A., & Gallivan, K. (2018). Graph learning for regularized low-rank matrix completion. MTNS 2018, 460-467. (Original work published 2018)
Olikier, G., Absil, P.-A., & De lathauwer, L. (2018). A variable projection method for block term decomposition of higher-order tensors. ESANN 2018 Proceedings. Published. 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges, Belgium.
Absil, P.-A., Sluysmans, B., & Stevens, N. (2018). MIQP-Based Algorithm for the Global Solution of Economic Dispatch Problems with Valve-Point Effects. 2018 Power Systems Computation Conference (PSCC), p. 1-7. https://doi.org/10.23919/pscc.2018.8450877
Olikier, G., Absil, P.-A., & De Lathauwer, L. (2018). Variable Projection Applied to Block Term Decomposition of Higher-Order Tensors. Latent Variable Analysis and Signal Separation : Lecture Notes in Computer Science, p. 139-148. https://doi.org/10.1007/978-3-319-93764-9_14
Papier de conférence
Gousenbourger, P.-Y., Jacques, L., & Absil, P.-A. (2017). Fast Method to Fit a C1 Piecewise-Bézier Function to Manifold-Valued Data Points: How Suboptimal is the Curve Obtained on the Sphere S2? In Nielsen F., Barbaresco F. (ed.), Geometric Science of Information. GSI 2017. Lecture Notes in Computer Science. Springer International. https://doi.org/10.1007/978-3-319-68445-1_69
Renard, E., & Absil, P.-A. (2017). Comparison of location-scale and matrix factorization batch effect removal methods on gene expression datasets. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), p. 1511-1518.
Gousenbourger, P.-Y., Massart, E., Musolas, A., Absil, P.-A., Hendrickx, J., Jacques, L., & Marzouk, Y. (2017). Piecewise-Bezier C1 smoothing on manifolds with application to wind field estimation. 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2017), 305-3010.
Dong, S., Thanou, D., Absil, P.-A., & Frossard, P. (2017). Learning sparse models of diffusive graph signals. Computational Intelligence and Machine learning, p. 251-256.
Article de journal
Massart, E., Hendrickx, J., & Absil, P.-A. (2017). Matrix geometric means based on shuffled inductive sequences. Linear Algebra and Its Applications, 252, 334-359. https://doi.org/10.1016/j.laa.2017.05.036 (Original work published 2018)
Gomez Gonzalez, C. A., Wertz, O., Absil, O., Christiaens, V., Defrère, D., Mawet, D., Milli, J., Absil, P.-A., Van Droogenbroeck, M., Cantalloube, F., Hinz, P. M., Skemer, A. J., Karlsson, M., & Surdej, J. (2017). VIP: Vortex Image Processing Package for High-contrast Direct Imaging. The Astronomical Journal, 154, 7. https://doi.org/10.3847/1538-3881/aa73d7 (Original work published 2017)
Papier de conférence
Huang, W., Absil, P.-A., & Gallivan, K. A. (2016). A Riemannian BFGS method for nonconvex optimization problems. Lecture Notes in Computational Science and Engineering, 112, 627-634. https://doi.org/10.1007/978-3-319-39929-4_60 (Original work published 2016)
Yuan, X., Huang, W., Absil, P.-A., & Gallivan, K. A. (2016). A Riemannian limited-memory BFGS algorithm for computing the matrix geometric mean. Proceedings of the International Conference on Computational Science. Published. ICCS 2016, San Diego, California, 6-8 June 2016. https://doi.org/10.1016/j.procs.2016.05.534
Renard, E., Teschendorff, A. E., & Absil, P.-A. (2016). Spatiotemporal ICA improves the selection of differentially expressed genes. Proceedings of the 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 301-306.
Gousenbourger, P.-Y., Absil, P.-A., Wirth, B., & Jacques, L. (2016). Interpolation on manifolds using Bézier functions. Proceedings of the third “international Traveling Workshop on Interactions between Sparse models and Technology” iTWIST′16. Published. “International Traveling Workshop on Interactions Between Sparse Models and Technology”, Aalborg, Denmark. (Original work published 2016)
Renard, E., Branders, S., & Absil, P.-A. (2016). Independent component analysis to remove batch effects from merged microarray datasets. Lecture Notes in Computer Science, 9838, 281-292. https://doi.org/10.1007/978-3-319-43681-4_23 (Original work published 2016)
Genicot, M., Absil, P.-A., Lambiotte, R., & Sami, S. (2016). Coupled tensor decomposition: A step towards robust components. 2016 24th European Signal Processing Conference (EUSIPCO), p. 1308-1312. https://doi.org/10.1109/eusipco.2016.7760460
Massart, E., Hendrickx, J., & Absil, P.-A. (2016). Extending a two-variable mean to a multi-variable mean. ESANN 2016, Bruges, Belgium, 26-28 April 2016.
Article de journal
Zhou, G., Huang, W., Gallivan, K. A., Van Dooren, P., & Absil, P.-A. (2016). A Riemannian rank-adaptive method for low-rank optimization. Neurocomputing, 192, 72-80. https://doi.org/10.1016/j.neucom.2016.02.030 (Original work published 2016)
Absil, P.-A., Gousenbourger, P.-Y., Striewski, P., & Wirth, B. (2016). Differentiable piecewise-Bézier surfaces on Riemannian manifolds. SIAM Journal on Imaging Sciences, 9(4), 1788-1828. https://doi.org/10.1137/16M1057978 (Original work published 2016)
Huang, W., Absil, P.-A., & Gallivan, K. A. (2016). Intrinsic representation of tangent vectors and vector transport on matrix manifolds. Numerische Mathematik, 136(2), 523-543. https://doi.org/10.1007/s00211-016-0848-4 (Original work published 2016)
Gomez Gonzalez, C., Absil, O., Absil, P.-A., Van Droogenbroeck, M., Mawet, D., & Surdej, J. (2016). Low-rank plus sparse decomposition for exoplanet detection in direct imaging ADI sequences. Astronomy & Astrophysics, 589. https://doi.org/10.1051/0004-6361/201527387 (Original work published 2016)
Cambier, L., & Absil, P.-A. (2016). Robust low-rank matrix completion by Riemannian optimization. SIAM Journal on Scientific Computing, 38(5), S440-S460. https://doi.org/10.1137/15M1025153 (Original work published 2016)
Papier de conférence
Zhou, G., Huang, W., Gallivan, K. A., Van Dooren, P., & Absil, P.-A. (2015). Rank-constrained Optimization: A Riemannian Manifold Approach. 23th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Bruges, Belgium, April 2015.
Huang, W., You, Y., Gallivan, K. A., & Absil, P.-A. (2015). Karcher mean in elastic shape analysis. In H. Drira, S. Kurtek, P. Turaga (Eds) (ed.), Proceedings of the 1st International Workshop on DIFFerential Geometry in Computer Vision for Analysis of Shapes, Images and Trajectories (DIFF-CV 2015) (p. 2). BMVA Press.
You, Y., Huang, W., Gallivan, K. A., & Absil, P.-A. (2015). A Riemannian approach for computing geodesics in elastic shape analysis. 2015 IEEE Global Conference on Signal and Information Processing, p. 727-731. https://doi.org/10.1109/GlobalSIP.2015.7418292
Arnould, A., Gousenbourger, P.-Y., Samir, C., Absil, P.-A., & Canis, M. (2015). Fitting Smooth Paths on Riemannian Manifolds: Endometrial Surface Reconstruction and Preoperative MRI-Based Navigation. Geometric Science of Information: second International Conference, GSI 2015, Palaiseau, France, October 28-30, 2015, Proceedings. Published. GSI 2015, Paris, Ecole Polytechnique. https://doi.org/10.1007/978-3-319-25040-3
Article de journal
Huang, W., Gallivan, K. A., Srivastava, A., & Absil, P.-A. (2015). Riemannian Optimization for Registration of Curves in Elastic Shape Analysis. Journal of Mathematical Imaging and Vision, 54(3), 320-343. https://doi.org/10.1007/s10851-015-0606-8 (Original work published 2016)
Absil, P.-A., & Oseledets, I. V. (2015). Low-rank retractions: a survey and new results. Computational Optimization and Applications : an international journal, 62(1), 5-29. https://doi.org/10.1007/s10589-014-9714-4 (Original work published 2015)
Huang, W., Gallivan, K. A., & Absil, P.-A. (2015). A Broyden Class of Quasi-Newton Methods for Riemannian Optimization. SIAM Journal on Optimization, 25(3), 1660-1685. https://doi.org/10.1137/140955483 (Original work published 2015)
Boumal, N., & Absil, P.-A. (2015). Low-rank matrix completion via preconditioned optimization on the Grassmann manifold. Linear Algebra and Its Applications, 475, 200-239. https://doi.org/10.1016/j.laa.2015.02.027 (Original work published 2015)
Article de journal
Borckmans, P., Suviseshamuthu, E. S., Boumal, N., & Absil, P.-A. (2014). A Riemannian Subgradient Algorithm for Economic Dispatch with Valve-Point Effect. Journal of Computational and Applied Mathematics, 255, 848-866. https://doi.org/10.1016/j.cam.2013.07.002 (Original work published 2014)
Boumal, N., Mishra, B., Absil, P.-A., & Sepulchre, R. (2014). Manopt, a Matlab toolbox for optimization on manifolds. Journal of Machine Learning Research, 15, 1455-1459. (Original work published 2014)
Pompili, F., Gillis, N., Absil, P.-A., & Glineur, F. (2014). Two algorithms for orthogonal nonnegative matrix factorization with application to clustering. Neurocomputing, 141, 15-25. https://doi.org/10.1016/j.neucom.2014.02.018 (Original work published 2014)
Boumal, N., Sepulchre, R., Absil, P.-A., & Mishra, B. (2014). Manopt, a matlab toolbox for optimization on manifolds. Journal of Machine Learning Research, 15, 1455-1459. (Original work published 2014)
Huang, W., Absil, P.-A., & Gallivan, K. A. (2014). A Riemannian symmetric rank-one trust-region method. Mathematical Programming, 150(2), 179-2016. https://doi.org/10.1007/s10107-014-0765-1 (Original work published 2014)
Winternitz, L. B., Tits, A. L., & Absil, P.-A. (2014). Addressing rank degeneracy in constraint-reduced interior-point methods for linear optimization. Journal of Optimization Theory and Applications, 160(1), 127-157. https://doi.org/10.1007/s10957-013-0323-7 (Original work published 2013)
Lefèvre, A., Glineur, F., & Absil, P.-A. (2014). A convex formulation for informed source separation in the single channel setting. Neurocomputing, 141, 26-36. https://doi.org/10.1016/j.neucom.2013.12.053 (Original work published 2014)
Boumal, N., Singer, A., Absil, P.-A., & Blondel, V. (2014). Cramér-Rao bounds for synchronization of rotations. Institute of Mathematics and Its Applications. Journal, 3(1), 1-39. https://doi.org/10.1093/imaiai/iat006 (Original work published 2013)
Absil, P.-A., Amodei, L., & Meyer, G. (2014). Two Newton methods on the manifold of fixed-rank matrices endowed with Riemannian quotient geometries. Computational Statistics, 29(3-4), 569-590. https://doi.org/10.1007/s00180-013-0441-6 (Original work published 2013)
Papier de conférence
Renard, E., Teschendorff, A. E., & Absil, P.-A. (2014). Capturing confounding sources of variation in DNA methylation data by spatiotemporal independent component analysis. 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Published. ESANN 2014, Bruges, Belgium, April 2014.
Huang, W., Gallivan, K. A., Srivastava, A., & Absil, P.-A. (2014). Riemannian Optimization for Elastic Shape Analysis. MTNS 2014, Groningen, The Netherlands.
Gousenbourger, P.-Y., Samir, C., & Absil, P.-A. (2014). Piecewise-Bézier C¹ interpolation on Riemannian manifolds with application to 2D shape morphing. ICPR2014, Stockholm.
Absil, O., Mawet, D., Delacroix, C., Forsberg, P., Karlsson, M., Habraken, S., Surdej, J., Absil, P.-A., Carlomagno, B., Christiaens, V., Defrère, D., Gomez Gonzalez, C. A., Huby, E., Jolivet, A., Milli, J., Piron, P., Vargas Catalan, E., & Van Droogenbroeck, M. (2014). The VORTEX project: first results and perspectives. In Enrico Marchetti ; Laird M. Close ; Jean-Pierre Véran (ed.), Proceedings SPIE 9148: Adaptive Optics Systems IV. https://doi.org/10.1117/12.2055702
Dorcimont, C., & Absil, P.-A. (2014). Algorithms for the nearest correlation matrix problem with factor structure. Book of Abstracts of the Householder Symposium XIX on Numerical Linear Algebra, p. 7-8.
Chapitre de livre
Teschendorff, A. E., Renard, E., & Absil, P.-A. (2014). Supervised normalization of large-scale omic datasets using blind source separation. In Ganesh R. Naik, Wenwu Wang (Eds.) (ed.), Blind source separation (p. p. 465-497). Springer. https://doi.org/10.1007/978-3-642-55016-4_17
Papier de conférence
Lefèvre, A., Glineur, F., & Absil, P.-A. (2013). A nuclear-norm based convex formulation for informed source separation. Proceedings of the 21st European Symposium on Artificial Neural Networks (ESANN 2013), 101-106.
Boumal, N., Singer, A., & Absil, P.-A. (2013). Robust estimation of rotations from relative measurements by maximum likelihood. Proceedings of the 52nd IEEE Conference on Decision and Control. Published. CDC′13, Firenze, Italy. https://doi.org/10.1109/CDC.2013.6760038
Pompili, F., Gillis, N., Absil, P.-A., & Glineur, F. (2013). ONP-MF: An Orthogonal Nonnegative Matrix Factorization Algorithm with Application to Clustering. Proceedings of the 21st European Symposium on Artificial Neural Networks (ESANN 2013), p. 297-302.
Absil, P.-A., Mahony, R., & Trumpf, J. (2013). An extrinsic look at the Riemannian Hessian. In Nielsen, Frank and Barbaresco, Frédéric (ed.), Geometric Science of Information (pp. 361-368). Springer. https://doi.org/10.1007/978-3-642-40020-9_39
Article de journal
Suviseshamuthu, E. S., Borckmans, P., Absil, P.-A., & Chattopadhyay, A. (2013). Spherical Mesh Adaptive Direct Search for Separating Quasi-uncorrelated Sources by Range-based Independent Component Analysis. Neural Computation, 25(9), 2486-2522. https://doi.org/10.1162/NECO_a_00485 (Original work published 2013)
Vandereycken, B., Absil, P.-A., & Vandewalle, S. (2013). A Riemannian geometry with complete geodesics for the set of positive semidefinite matrices of fixed rank. IMA Journal of Numerical Analysis, 33, 481-514. https://doi.org/10.1093/imanum/drs006 (Original work published 2013)
Cason, T., Absil, P.-A., & Van Dooren, P. (2013). Iterative Methods for Low Rank Approximation of Graph Similarity Matrices. Linear Algebra and Its Applications, 438, 1863-1882. https://doi.org/10.1016/j.laa.2011.12.004 (Original work published 2013)
Ishteva, M., Absil, P.-A., & Van Dooren, P. (2013). Jacobi algorithm for the best low multilinear rank approximation of symmetric tensors. SIAM Journal on Matrix Analysis and Applications. Accepted/in-press. (Original work published 2013)
Chapitre de livre
Absil, P.-A., & Hochstenbach, M. E. (2013). A differential-geometric look at the Jacobi-Davidson framework. In K. Huper, J. Trumpf (eds) (ed.), Mathematical System Theory - Festschrift in Honor of Uwe Helmke on the Occasion of his Sixtieth Birthday (p. p. 11-22). CreateSpace.
Chapitre de livre
Gallivan, K. A., Qi, C., & Absil, P.-A. (2012). A Riemannian Dennis-Moré condition. In Michael W. Berry, Kyle A. Gallivan, Efstratios Gallopoulos, Ananth Grama, Bernard Philippe, Yousef Saad, Faisal Saied (ed.), High-Performance Scientific Computing - Algorithms and Applications (p. p. 281-293). Springer-Verlag. https://doi.org/10.1007/978-1-4471-2437-5_14
Papier de conférence
Boumal, N., Singer, A., & Absil, P.-A. (2012). Synchronization of rotations via Riemannian trust-regions. SIAM Conference on Applied Linear Algebra (SIAM/LA), Valencia, Spain.
Abedrabbo Ode, G., Absil, P.-A., Mahaudens, P., Detrembleur, C., Raison, M., Mousny, M., & Fisette, P. (2012). A multibody-based approach to the computation of spine intervertebral motions in scoliotic patients. The 2nd Joint International Conference on Multibody System Dynamics, Stuttgart, Germany.
Suviseshamuthu, E. S., Chattopadhyay, A., Amato, U., & Absil, P.-A. (2012). Range-based non-orthogonal ICA using cross-entropy method. Proceedings of the 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012), 519-524.
Boumal, N., Absil, P.-A., & Singer, A. (2012). Riemannian algorithms and estimation bounds for synchronization of rotations. International symposium on mathematical programming, Berlin.
Article de journal
Absil, P.-A., & Malick, J. (2012). Projection-like retractions on matrix manifolds. SIAM Journal on Optimization, 22(1), 135-158. https://doi.org/10.1137/100802529 (Original work published 2012)
Samir, C., Absil, P.-A., Srivastava, A., & Klassen, E. (2012). A Gradient-Descent Method for Curve Fitting on Riemannian Manifolds. Foundations of Computational Mathematics, 12(1), 49-73. https://doi.org/10.1007/s10208-011-9091-7 (Original work published 2012)
Abedrabbo Ode, G., Fisette, P., Absil, P.-A., Mahaudens, P., Detrembleur, C., Raison, M., Banse, X., Aubin, C.-E., & Mousny, M. (2012). A multibody-based approach to the computation of spine intervertebral motions in scoliotic patients. Studies in Health Technology and Informatics, 176, 95-98. (Original work published 2012)
Papier de conférence
Browet, A., Van Dooren, P., & Absil, P.-A. (2011). Community Detection for Hierarchical Image Segmentation. International workshop on combinatorial image analysis (IWCIA 2011), Madrid, Spain.
Rentmeesters, Q., & Absil, P.-A. (2011). Algorithm comparison for Karcher mean computation of rotation matrices and diffusion tensors. EUSIPCO 2011: 19th European Signal Processing Conference, 2229-2233. (Original work published 2011)
Boumal, N., & Absil, P.-A. (2011). Discrete curve fitting on manifolds. In Clara Ionescu et al. (eds.) (ed.), Book of Abstracts 30th Benelux Meeting on Systems and Control (p. 138). Universiteit Gent - Vakgroep Elektrische energie, Systemen en Automatisering.
Boumal, N., & Absil, P.-A. (2011). RTRMC: A Riemannian trust-region method for low-rank matrix completion. In J. Shawe-Taylor, R.S. Zemel, P. Bartlett, F.C.N. Pereira, K.Q. Weinberger (ed.), Advances in Neural Information Processing Systems 24 (pp. 406-414).
Boumal, N., & Absil, P.-A. (2011). Discrete regression methods on the cone of positive-definite matrices. 2011 IEEE International Conference on Acoustics, Speech and SignalProcessing (ICASSP), 4232-4235. https://doi.org/10.1109/ICASSP.2011.5947287
Ivanov, T., Anderson, B. D. O., Absil, P.-A., & Gevers, M. (2011). Information Inequality for Estimation of Transfer Functions: main results. Proceedings of the 18th IFAC World Congress. Published. 18th IFAC World Congress, Milano, Italy. https://doi.org/10.3182/20110828-6-IT-1002.00806
Boumal, N., & Absil, P.-A. (2011). A discrete regression method on manifolds and its application to data on SO(n). Proceedings of the 18th IFAC World Congress, 2011, 2284-2289. https://doi.org/10.3182/20110828-6-IT-1002.00542
Article de journal
Ishteva, M., Absil, P.-A., Van Huffel, S., & De Lathauwer, L. (2011). Best low multilinear rank approximation of higher-order tensors, based on the Riemannian trust-region scheme. SIAM Journal on Matrix Analysis and Applications, 32(1), 115-135. https://doi.org/10.1137/090764827 (Original work published 2011)
Ishteva, M., Absil, P.-A., Van Huffel, S., & De Lathauwer, L. (2011). Tucker compression and local optima. Chemometrics and Intelligent Laboratory Systems, 106(1), 57-64. https://doi.org/10.1016/j.chemolab.2010.06.006 (Original work published 2011)
Ivanov, T., Anderson, B. D. O., Absil, P.-A., & Gevers, M. (2011). New relations between norms of system transfer functions. Systems & Control Letters, 60(3), 151-155. https://doi.org/10.1016/j.sysconle.2010.10.008 (Original work published 2011)
Chapitre de livre
Cason, T., Absil, P.-A., & Van Dooren, P. (2011). Comparing Two Matrices by Means of Isometric Projections. In Van Dooren et al (ed.), Numerical Linear Algebra in Signals, Systems and Control (pp. 77-93). Springer Verlag. https://doi.org/10.1007/978-94-007-0602-6_4
Samir, C., Absil, P.-A., & Van Dooren, P. (2011). 2D and 3D Objects Morphing Using Shape Manifold Techniques. In Yun Fu (ed.), Manifold Learning Theory and Application (p. p. 209-231). CRC Press.
Chapitre de livre
Qi, C., Gallivan, K., & Absil, P.-A. (2010). Riemannian BFGS algorithm with applications. In Moritz Diehl (ed.), Recent Advances in Optimization and its Applications in Engineering (p. p. 183-192). Springer. https://doi.org/10.1007/978-3-642-12598-0_16
Journée, M., Bach, F. H., Absil, P.-A., & Sepulchre, R. (2010). Refining Sparse Principal Components. In Moritz Diehl (ed.), Recent Advances in Optimization and its Applications in Engineering (p. p. 165-171). Springer. https://doi.org/10.1007/978-3-642-12598-0_14
Rentmeesters, Q., Absil, P.-A., & Van Dooren, P. (2010). Identification method for time-varying ARX models. In Moritz Diehl (ed.), Recent Advances in Optimization and its Applications in Engineering (p. p. 193-202). Springer. https://doi.org/10.1007/978-3-642-12598-0_17
Ishteva, M., Absil, P.-A., Van Huffel, S., & De Lathauwer, L. (2010). On the best low multilinear rank approximation of higher-order tensors. In Moritz Diehl (ed.), Recent Advances in Optimization and its Applications in Engineering (p. p. 145-164). Springer. https://doi.org/10.1007/978-3-642-12598-0_13
Absil, P.-A., Mahony, R., & Sepulchre, R. (2010). Optimization On Manifolds: Methods And Applications. In Moritz Diehl, Francois Glineur, Elias Jarlebring, Wim Michiels (ed.), Recent Advances in Optimization and its Applications in Engineering : The 14th Belgian-French-German Conference on Optimization. Springer. https://doi.org/10.1007/978-3-642-12598-0_12
Papier de conférence
Cason, T., Absil, P.-A., Blondel, V., & Van Dooren, P. (2010). A Unified Framework for Affine Graph Similarity. 19th International Symposium on Mathematical Theory of Networks and Systems, 125-129.
Ishteva, M., Absil, P.-A., Van Huffel, S., & De Lathauwer, L. (2010). Local minima of the best low multilinear rank approximation of tensors. 19th Mathematical Symposium on Mathematical Theory of Networks and Systems, 2145-2146.
Ivanov, T., Absil, P.-A., & Gevers, M. (2010). The information inequality for function spaces given a singular information matrix. CD-ROM Proc. of 19th International Symp. on Mathematical Theory of Networks and Systems (MTNS 2010), Budapest, Hungary.
Qi, C., Gallivan, K., & Absil, P.-A. (2010). An Efficient BFGS Algorithm for Riemannian Optimization. 19th International Symposium on Mathematical Theory of Networks and Systems, 2221-2227.
Rentmeesters, Q., Absil, P.-A., & Van Dooren, P. (2010). A filtering technique on the Grassmann manifold. 19th International Symposium on Mathematical Theory of Networks and Systems, 2145-2146.
Ishteva, M., Absil, P.-A., Van Huffel, S., & De Lathauwer, L. (2010). Tensor- versus matrix-based algorithms in exponential data fitting (abstract). Book of Abstracts of the 29th Benelux Meeting on Systems and Control, p. 37.
Rentmeesters, Q., Absil, P.-A., Van Dooren, P., Gallivan, K., & Srivastava, A. (2010). An efficient particle filtering technique on the Grassmann manifold. 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2010, p. 3838-3841. https://doi.org/10.1109/ICASSP.2010.5495828
Winternitz, L. B., & Absil, P.-A. (2010). Primal-dual interior-point algorithms for linear programs with many inequality constraints. Book of abstracts of the 2nd IMA Conference on Numerical Linear Algebra and Optimisation, Birmingham, UK.
Borckmans, P., Ishteva, M., & Absil, P.-A. (2010). A Modified Particle Swarm Optimization Algorithm for the Best Low Multilinear Rank Approximation of Higher-Order Tensors. Swarm Intelligence, 13-23. https://doi.org/10.1007/978-3-642-15461-4_2
Ivanov, T., Gevers, M., Absil, P.-A., & Anderson, B. D. O. (2010). The Information Inequality on Function Spaces (abstract). Book of Abstracts of the 29th Benelux Meeting on Systems and Control, p. 52.
Browet, A., Van Dooren, P., & Absil, P.-A. (2010). Image segmentation and real-time video tracking using graph based techniques (abstract). Book of Abstracts of the 29th Benelux Meeting on Systems and Control, 101.
Borckmans, P., & Absil, P.-A. (2010). Fast Oriented Bounding Box Computation Using Particle Swarm Optimization (abstract). Book of Abstracts of the 29th Benelux Meeting on Systems and Control, 34.
Sepulchre, R., Absil, P.-A., & Bonnabel, S. (2010). Géométrie des matrices positives semi-définies de rang fixé : un peu de théorie et beaucoup d’applications. Sixième Conférence Internationale Francophone d’Automatique (CIFA 2010), Nancy, France.
Cason, T., Absil, P.-A., & Van Dooren, P. (2010). Review of Similarity Matrices and Application to Subgraph Matching (abstract). Book of Abstracts of the 29th Benelux Meeting on Systems and Control, 109.
Rentmeesters, Q., Absil, P.-A., & Van Dooren, P. (2010). A filtering technique on the Grassmann manifold (abstract). Book of Abstracts of the 29th Benelux Meeting on Systems and Control, 178.
Article de journal
Absil, P.-A., & Van Dooren, P. (2010). Two-sided Grassmann-Rayleigh quotient iteration. Numerische Mathematik, 114, 549-571. https://doi.org/10.1007/s00211-009-0266-y (Original work published 2010)
Staes, E., Absil, P.-A., Lins, L., Brasseur, R., Deleu, M., Lecouturier, N., Fievez, V., des Rieux, A., Mingeot-Leclercq, M.-P., Raussens, V., & Préat, V. (2010). Acylated and unacylated ghrelin binding to membranes and to ghrelin receptor : towards a better understanding of the underlying mechanisms. BBA - Biomembranes, 1798(11), 2102-2113. https://doi.org/10.1016/j.bbamem.2010.07.002 (Original work published 2010)
Van Dooren, P., Gallivan, K., & Absil, P.-A. (2010). H2-optimal model reduction with higher-order poles. SIAM Journal on Matrix Analysis and Applications, 31(5), 2738. https://doi.org/10.1137/080731591 (Original work published 2010)
Journée, M., Bach, F., Absil, P.-A., & Sepulchre, R. (2010). Low-rank Optimization On the Cone of Positive Semidefinite Matrices. SIAM Journal on Optimization, 20(5), 2327-2351. https://doi.org/10.1137/080731359 (Original work published 2010)
Article de journal
Ishteva, M., De Lathauwer, L., Absil, P.-A., & Van Huffel, S. (2009). Differential-geometric Newton method for the best rank-(R (1), R (2), R (3)) approximation of tensors. Numerical Algorithms, 51(2), 179-194. https://doi.org/10.1007/s11075-008-9251-2 (Original work published 2009)
Absil, P.-A., & Gallivan, K. A. (2009). Accelerated Line-search and Trust-region Methods. SIAM Journal on Numerical Analysis, 47(2), 997-1018. https://doi.org/10.1137/08072019X (Original work published 2009)
Papier de conférence
Qi, C., Gallivan, K. A., & Absil, P.-A. (2009). The Riemannian BFGS algorithm with applications (abstract). Book of Abstracts of the 14th Belgian-French-German Conference on Optimization (BFG′09), p. 57.
Samir, C., Absil, P.-A., Srivastava, A., & Klassen, E. (2009). Fitting smooth curves on a Riemannian manifold (abstract). In J. De Schutter, M. Diehl, F. Glineur, E. Jarlebring, Q. Louveaux, W. Michiels, I. Smets, J. Suykens, J. Swevers, J. Vandewalle, J. Van Impe, M. Verschuure (ed.), Book of Abstracts of the 14th Belgian-French-German Conference on Optimization (BFG′09) (p. p. 55).
Samir, C., Van Dooren, P., Laurent, D., Gallivan, K., & Absil, P.-A. (2009). Elastic Morphing of 2D and 3D Objects on a Shape Manifold. Image Analysis and Recognition - Proceedings of the 6th International Conference (ICIAR 2009) - Lecture Notes in Computer Science Vol. 5627/2009, Halifax, Canada. https://doi.org/10.1007/978-3-642-02611-9
Vandereycken, B., Absil, P.-A., & Vandewalle, S. (2009). Embedded geometry of the set of symmetric positive semidefinite matrices of fixed rank. Proceedings of the 15th Workshop on Statistical Signal Processing (SSP ’09), p. 389-392. https://doi.org/10.1109/SSP.2009.5278558
Samir, C., Absil, P.-A., Srivastava, A., & Klassen, E. (2009). Fitting Curves on Riemannian Manifolds Using Energy Minimization. Proceedings of the eleventh IAPR Conference on Machine Vision Applications MVA2009, p. 422-425.
Theis, F. J., Cason, T., & Absil, P.-A. (2009). Soft dimension reduction for ICA by joint diagonalization on the Stiefel manifold. Independent Component Analysis and Signal Separation, p. 354-361. https://doi.org/10.1007/978-3-642-00599-2_45
Absil, P.-A. (2009). Optimization on manifolds: methods and applications (abstract). 14 th Belgian-French-German Conference on Optimization - Book of Abstracts, p. 51.
Ivanov, T., Anderson, B. D. O., Absil, P.-A., & Gevers, M. (2009). Using H2 norm to bound H-infinity norm from above on Real Rational Modules. Proceedings of the European Control Conference 2009, p. 2259-2264.
Borckmans, P., & Absil, P.-A. (2009). Fast Oriented Bounding Box Computation Using Particle Swarm Optimization. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2010), Bruges, Belgium.
Journée, M., Bach, F. H., Absil, P.-A., & Sepulchre, R. (2009). Optimization on low-rank positive semidefinite matrices (abstract). In J. De Schutter, M. Diehl, F. Glineur, E. Jarlebring, Q. Louveaux, W. Michiels, I. Smets, J. Suykens, J. Swevers, J. Vandewalle, J. Van Impe, M. Verschuure (ed.), Book of Abstracts of the 14th Belgian-French-German Conference on Optimization (BFG′09) (p. p. 71).
Sainlez, M., Absil, P.-A., & Teschendorff, A. E. (2009). Gene expression data analysis using spatiotemporal blind source separation. ESANN 2009 proceedings, p. 159-164.
Article de journal
Absil, P.-A., Ishteva, M., De Lathauwer, L., & Van Huffel, S. (2008). A Geometric Newton Method for Oja’s Vector Field. Neural Computation, 21(5), 1415-1433. https://doi.org/10.1162/neco.2008.04-08-749 (Original work published 2009)
Baker, C. G., Absil, P.-A., & Gallivan, K. A. (2008). An implicit trust-region method on Riemannian manifolds. IMA Journal of Numerical Analysis, 28(4), 665-689. https://doi.org/10.1093/imanum/drn029 (Original work published 2008)
Absil, P.-A., Sepulchre, R., & Mahony, R. (2008). Continuous-time subspace flows related to the symmetric eigenproblem. Pacific Journal of Optimization, 4(2), 179-194. (Original work published 2008)
Ishteva, M., De Lathauwer, L., & Absil, P.-A. (2008). Dimensionality reduction for higher-order tensors: algorithms and applications. International Journal of Pure and Applied Mathematics, 42(3), 337-343. (Original work published 2008)
Absil, P.-A. (2008). Numerical representations of a universal subspace flow for linear programs. Communications in Information and Systems, 8(2), 71-84. https://doi.org/10.4310/CIS.2008.v8.n2.a2 (Original work published 2008)
Van Dooren, P., Gallivan, K., & Absil, P.-A. (2008). H2-optimal model reduction of MIMO systems. Applied Mathematics Letters, 21(12), 1267-1273. https://doi.org/10.1016/j.aml.2007.09.015 (Original work published 2008)
Papier de conférence
Ishteva, M., De Lathauwer, L., Absil, P.-A., & Van Huffel, S. (2008). The best rank-(R1,R2,R3) approximation of tensors by means of a geometric Newton method. Numerical Analysis and Applied Mathematics, p. 274-277. https://doi.org/10.1063/1.2990911
Ivanov, T., Absil, P.-A., Anderson, B., & Gevers, M. (2008). Application of real rational modules in system identification. 2008 47th IEEE Conference on Decision and Control, p. 111-116. https://doi.org/10.1109/CDC.2008.4738869
Monographie
Absil, P.-A., Mahony, R., & Sepulchre, R. (2008). Optimization Algorithms on Matrix Manifolds. Princeton University Press.
Papier de conférence
Journée, M., Teschendorff, A. E., Absil, P.-A., & Sepulchre, R. (2007). Geometric optimization methods for independent component analysis applied on gene expression data. 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, p. IV-1413 - IV-1416. https://doi.org/10.1109/ICASSP.2007.367344
Journée, M., Absil, P.-A., & Sepulchre, R. (2007). Optimization on the orthogonal group for independent component analysis. In Mike E. Davies, Christopher J. James, Samer A. Abdallah and Mark D Plumbley (ed.), Independent Component Analysis and Signal Separation (p. p. 57-64). Springer-Verlag. https://doi.org/10.1007/978-3-540-74494-8
Absil, P.-A., Lageman, C., & Manton, J. H. (2007). Design of continuous-time flows on intertwined orbit spaces. Proceedings of the 46th IEEE Conference on Decision and Control, p. 6244-6249. https://doi.org/10.1109/CDC.2007.4434712
Chapitre de livre
Journée, M., Teschendorff, A. E., Absil, P.-A., Tavaré, S., & Sepulchre, R. (2007). Geometric optimization methods for the analysis of gene expression data. In eds. A. Gorban, B. Kegl, D. Winsch, A. Zinovyev, (ed.), Principal Manifolds for Data Visualisation and Dimension Reduction (p. p. 271-292). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-73750-6_12
Article de journal
Absil, P.-A., Baker, C. G., & Gallivan, K. A. (2007). Trust-region methods on Riemannian manifolds. Foundations of Computational Mathematics, 7(3), 303-330. https://doi.org/10.1007/s10208-005-0179-9 (Original work published 2007)
Teschendorff, A. E., Journée, M., Absil, P.-A., Sepulchre, R., & Caldas, C. (2007). Elucidating the Altered Transcriptional Programs in Breast Cancer using Independent Component Analysis. PLoS Computational Biology, 3(8), e161. https://doi.org/10.1371/journal.pcbi.0030161 (Original work published 2007)
Absil, P.-A., & Tits, A. L. (2007). Newton-KKT interior-point methods for indefinite quadratic programming. Computational Optimization and Applications : an international journal, 36(1), 5-41. https://doi.org/10.1007/s10589-006-8717-1 (Original work published 2007)
Papier de conférence
Absil, P.-A., & Gallivan, K. A. (2006). Joint diagonalization on the oblique manifold for independent component analysis. Proceedings of the 2006 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), p. V-945 - V-948. https://doi.org/10.1109/ICASSP.2006.1661433
Baker, C. G., Absil, P.-A., & Gallivan, K. A. (2006). An implicit Riemannian Trust-Region method for the symmetric generalized eigenproblem. In Alexandrov, VN; VanAlbada, GD; Sloot, PMA; Dongarra, J (ed.), Proceedings of the 6th International Conference on Computational Science (pp. 210-217). Springer-verlag Berlin. https://doi.org/10.1007/11758501_32
Article de journal
Absil, P.-A. (2006). Continuous-time systems that solve computational problems. International Journal of Unconventional Computing, 2(4), 291-304. (Original work published 2006)
Absil, P.-A., Baker, C., & Gallivan, K. (2006). A truncated-CG style method for symmetric generalized eigenvalue problems. Journal of Computational and Applied Mathematics.
Absil, P.-A., Edelman, A., & Koev, P. (2006). On the largest principal angle between random subspaces. Linear Algebra and Its Applications, 414(1), 288-294. https://doi.org/10.1016/j.laa.2005.10.004 (Original work published 2006)
Tits, A., Absil, P.-A., & Woessner, W. P. (2006). Constraint reduction for linear programs with many inequality constraints. SIAM Journal on Optimization, 17(1), 119. https://doi.org/10.1137/050633421 (Original work published 2006)
Absil, P.-A., & Kurdyka, K. (2006). On the stable equilibrium points of gradient systems. Systems & Control Letters, 55(7), 573-577. https://doi.org/10.1016/j.sysconle.2006.01.002 (Original work published 2006)
Article de journal
Absil, P.-A., Mahony, R., & Andrews, B. (2005). Convergence of the iterates of descent methods for analytic cost functions. SIAM Journal on Optimization, 16(2), 531-547. https://doi.org/10.1137/040605266 (Original work published 2005)
Papier de conférence
Absil, P.-A., Baker, C. G., Gallivan, K. A., & Sameh, A. (2005). Adaptive model trust region methods for generalized eigenvalue problems. In V.S. Sunderam et al. (ed.), Computational Science - ICCS 2005 (p. p. 33-41). https://doi.org/10.1007/11428831_5
Article de journal
Absil, P.-A., Sepulchre, R., Van Dooren, P., & Mahony, R. (2004). Cubically convergent iterations for invariant subspace computation. SIAM Journal on Matrix Analysis and Applications, 26(1), 70-96. https://doi.org/10.1137/S0895479803422002 (Original work published 2004)
Papier de conférence
Absil, P.-A., Sepulchre, R., Van Dooren, P., & Mahony, R. (2003). A newton algorithm for invariant subspace computation with large basins of attraction. Conference on Decision and Control (CDC 2003), Hawaii, USA.
Article de journal
Absil, P.-A., Mahony, R., Sepulchre, R., & Van Dooren, P. (2002). A Grassmann-Rayleigh quotient iteration for computing invariant subspaces. SIAM Review, 44(1), 57-73. https://doi.org/10.1137/S0036144500378648 (Original work published 2002)
Papier de conférence
Absil, P.-A., Mahony, R., Sepulchre, R., & Van Dooren, P. (2000). A Grasmann-Rayleigh quotient iteration for computing invariant subspaces. 39th Conferece on Decision and Control, CDC, Sydney.
