| Convex analysis and monotone operator theory in Hilbert spaces HH Bauschke, PL Combettes Convex Analysis and Monotone Operator Theory in Hilbert Spaces, 2nd edition., 2017 | 6677* | 2017 |
| Signal recovery by proximal forward-backward splitting PL Combettes, VR Wajs Multiscale modeling & simulation 4 (4), 1168-1200, 2005 | 3433 | 2005 |
| Proximal splitting methods in signal processing PL Combettes, JC Pesquet Fixed-point algorithms for inverse problems in science and engineering, 185-212, 2011 | 3198 | 2011 |
| Equilibrium programming in Hilbert spaces PL Combettes, SA Hirstoaga J. Nonlinear Convex Anal 6 (1), 117-136, 2005 | 1404 | 2005 |
| The foundations of set theoretic estimation PL Combettes Proceedings of the IEEE 81 (2), 182-208, 1993 | 872 | 1993 |
| Phase retrieval, error reduction algorithm, and Fienup variants: a view from convex optimization HH Bauschke, PL Combettes, DR Luke Journal of the Optical Society of America A 19 (7), 1334-1345, 2002 | 726 | 2002 |
| The convex feasibility problem in image recovery PL Combettes Advances in imaging and electron physics 95, 155-270, 1996 | 626 | 1996 |
| A Douglas–Rachford splitting approach to nonsmooth convex variational signal recovery PL Combettes, JC Pesquet IEEE Journal of Selected Topics in Signal Processing 1 (4), 564-574, 2007 | 614 | 2007 |
| Solving monotone inclusions via compositions of nonexpansive averaged operators PL Combettes* Optimization 53 (5-6), 475-504, 2004 | 538 | 2004 |
| A weak-to-strong convergence principle for Fejér-monotone methods in Hilbert spaces HH Bauschke, PL Combettes Mathematics of operations research 26 (2), 248-264, 2001 | 536 | 2001 |
| Primal-dual splitting algorithm for solving inclusions with mixtures of composite, Lipschitzian, and parallel-sum type monotone operators PL Combettes, JC Pesquet Set-Valued and variational analysis 20 (2), 307-330, 2012 | 467 | 2012 |
| Essential smoothness, essential strict convexity, and Legendre functions in Banach spaces HH Bauschke, JM Borwein, PL Combettes Communications in Contemporary Mathematics 3 (04), 615-647, 2001 | 393 | 2001 |
| Bregman monotone optimization algorithms HH Bauschke, JM Borwein, PL Combettes SIAM Journal on control and optimization 42 (2), 596-636, 2003 | 380 | 2003 |
| Fixed-point algorithms for inverse problems in science and engineering HH Bauschke, RS Burachik, PL Combettes, V Elser, DR Luke, ... Springer Science & Business Media, 2011 | 344 | 2011 |
| A proximal decomposition method for solving convex variational inverse problems PL Combettes, JC Pesquet Inverse problems 24 (6), 065014, 2008 | 344 | 2008 |
| A variational formulation for frame-based inverse problems C Chaux, PL Combettes, JC Pesquet, VR Wajs Inverse Problems 23 (4), 1495, 2007 | 317 | 2007 |
| Quasi-Fejérian analysis of some optimization algorithms PL Combettes Studies in Computational Mathematics 8, 115-152, 2001 | 313 | 2001 |
| Hybrid projection–reflection method for phase retrieval HH Bauschke, PL Combettes, DR Luke Journal of the Optical Society of America A 20 (6), 1025-1034, 2003 | 299 | 2003 |
| A monotone+ skew splitting model for composite monotone inclusions in duality LM Briceno-Arias, PL Combettes SIAM Journal on Optimization 21 (4), 1230-1250, 2011 | 296 | 2011 |
| Image restoration subject to a total variation constraint PL Combettes, JC Pesquet IEEE transactions on image processing 13 (9), 1213-1222, 2004 | 277 | 2004 |
Heinz H. BauschkeProfessor of Mathematics, University of British ColumbiaVerified email at ubc.ca
