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Patrick L. Combettes
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2020 – today
- 2024
- [j62]Patrick L. Combettes
:
The geometry of monotone operator splitting methods. Acta Numer. 33: 487-632 (2024) - [j61]Luis M. Briceño-Arias, Patrick L. Combettes
A Perturbation Framework for Convex Minimization and Monotone Inclusion Problems with Nonlinear Compositions. Math. Oper. Res. 49(3): 1890-1914 (2024) - [j60]Luis M. Briceño-Arias
Proximity Operators of Perspective Functions with Nonlinear Scaling. SIAM J. Optim. 34(4): 3212-3234 (2024) - [c45]Patrick L. Combettes, Diêgo J. Cornejo:
Signal Recovery with Proximal Comixtures. EUSIPCO 2024: 2637-2641 - [c44]Patrick L. Combettes, Javier I. Madariaga:
Randomly Activated Proximal Methods for Nonsmooth Convex Minimization. EUSIPCO 2024: 2642-2646 - 2023
- [c43]Patrick L. Combettes, Jean-Christophe Pesquet, Audrey Repetti
A Variational Inequality Model for Learning Neural Networks. ICASSP 2023: 1-5 - 2022
- [j59]Minh N. Bùi
Multivariate Monotone Inclusions in Saddle Form. Math. Oper. Res. 47(2): 1082-1109 (2022) - [j58]Patrick L. Combettes
A Variational Inequality Model for the Construction of Signals from Inconsistent Nonlinear Equations. SIAM J. Imaging Sci. 15(1): 84-109 (2022) - [c42]Minh N. Bùi, Patrick L. Combettes
Block-Activated Algorithms For Multicomponent Fully Nonsmooth Minimization. ICASSP 2022: 5428-5432 - [c41]Patrick L. Combettes
Signal Recovery from Inconsistent Nonlinear Observations. ICASSP 2022: 5872-5876 - 2021
- [j57]Patrick L. Combettes
Reconstruction of functions from prescribed proximal points. J. Approx. Theory 268: 105606 (2021) - [j56]Léo Simpson, Patrick L. Combettes, Christian L. Müller
c-lasso - a Python package for constrained sparse and robust regression and classification. J. Open Source Softw. 6(57): 2844 (2021) - [j55]Patrick L. Combettes
Fixed Point Strategies in Data Science. IEEE Trans. Signal Process. 69: 3878-3905 (2021) - 2020
- [j54]Nhut Minh Bùi
The Douglas-Rachford Algorithm Converges Only Weakly. SIAM J. Control. Optim. 58(2): 1118-1120 (2020) - [j53]Patrick L. Combettes
Lipschitz Certificates for Layered Network Structures Driven by Averaged Activation Operators. SIAM J. Math. Data Sci. 2(2): 529-557 (2020) - [c40]Patrick L. Combettes
A Fixed Point Framework for Recovering Signals from Nonlinear Transformations. EUSIPCO 2020: 2120-2124 - [i1]Léo Simpson, Patrick L. Combettes, Christian L. Müller:
c-lasso - a Python package for constrained sparse and robust regression and classification. CoRR abs/2011.00898 (2020)
2010 – 2019
- 2019
- [j52]Patrick L. Combettes
Stochastic quasi-Fejér block-coordinate fixed point iterations with random sweeping II: mean-square and linear convergence. Math. Program. 174(1-2): 433-451 (2019) - [j51]Patrick L. Combettes
Learning with optimal interpolation norms. Numer. Algorithms 81(2): 695-717 (2019) - [j50]Patrick L. Combettes
Proximal Activation of Smooth Functions in Splitting Algorithms for Convex Image Recovery. SIAM J. Imaging Sci. 12(4): 1905-1935 (2019) - [c39]Patrick L. Combettes
Fully Proximal Splitting Algorithms In Image Recovery. EUSIPCO 2019: 1-5 - 2018
- [j49]Patrick L. Combettes
Consistent learning by composite proximal thresholding. Math. Program. 167(1): 99-127 (2018) - [j48]Patrick L. Combettes
Asynchronous block-iterative primal-dual decomposition methods for monotone inclusions. Math. Program. 168(1-2): 645-672 (2018) - [j47]Patrick L. Combettes
Monotone operator theory in convex optimization. Math. Program. 170(1): 177-206 (2018) - [c38]Patrick L. Combettes
Linear Convergence of Stochastic Block-Coordinate Fixed Point Algorithms. EUSIPCO 2018: 742-746 - 2017
- [j46]Patrick L. Combettes
Quasi-Nonexpansive Iterations on the Affine Hull of Orbits: From Mann's Mean Value Algorithm to Inertial Methods. SIAM J. Optim. 27(4): 2356-2380 (2017) - [j45]Michel Barlaud, Wafa Belhajali, Patrick L. Combettes
Classification and Regression Using an Outer Approximation Projection-Gradient Method. IEEE Trans. Signal Process. 65(17): 4635-4644 (2017) - 2016
- [j44]Hédy Attouch, Luis M. Briceño-Arias
A strongly convergent primal-dual method for nonoverlapping domain decomposition. Numerische Mathematik 133(3): 443-470 (2016) - [c37]Patrick L. Combettes
Stochastic forward-backward and primal-dual approximation algorithms with application to online image restoration. EUSIPCO 2016: 1813-1817 - 2015
- [j43]Patrick L. Combettes
Stochastic Quasi-Fejér Block-Coordinate Fixed Point Iterations with Random Sweeping. SIAM J. Optim. 25(2): 1221-1248 (2015) - 2014
- [j42]Patrick L. Combettes
Preface. Math. Program. 148(1-2): 1-4 (2014) - [j41]Maryam A. Alghamdi, Abdullah M. Alotaibi
A primal-dual method of partial inverses for composite inclusions. Optim. Lett. 8(8): 2271-2284 (2014) - [j40]Abdullah M. Alotaibi
Solving Coupled Composite Monotone Inclusions by Successive Fejér Approximations of their Kuhn-Tucker Set. SIAM J. Optim. 24(4): 2076-2095 (2014) - [c36]Patrick L. Combettes
A forward-backward view of some primal-dual optimization methods in image recovery. ICIP 2014: 4141-4145 - 2013
- [j39]Patrick L. Combettes
Moreau's decomposition in Banach spaces. Math. Program. 139(1-2): 103-114 (2013) - [j38]Patrick L. Combettes
Systems of Structured Monotone Inclusions: Duality, Algorithms, and Applications. SIAM J. Optim. 23(4): 2420-2447 (2013) - 2012
- [j37]Yair Censor
On the effectiveness of projection methods for convex feasibility problems with linear inequality constraints. Comput. Optim. Appl. 51(3): 1065-1088 (2012) - 2011
- [b1]Heinz H. Bauschke, Patrick L. Combettes
Convex Analysis and Monotone Operator Theory in Hilbert Spaces. CMS Books in Mathematics, Springer 2011, ISBN 978-1-4419-9466-0, pp. 1-468 - [j36]Luis M. Briceño-Arias
Proximal Algorithms for Multicomponent Image Recovery Problems. J. Math. Imaging Vis. 41(1-2): 3-22 (2011) - [j35]Luis M. Briceño-Arias
A Monotone+Skew Splitting Model for Composite Monotone Inclusions in Duality. SIAM J. Optim. 21(4): 1230-1250 (2011) - [p1]Patrick L. Combettes
Proximal Splitting Methods in Signal Processing. Fixed-Point Algorithms for Inverse Problems in Science and Engineering 2011: 185-212 - [e1]Heinz H. Bauschke, Regina Sandra Burachik
Fixed-Point Algorithms for Inverse Problems in Science and Engineering. Springer Optimization and Its Applications 49, Springer 2011, ISBN 978-1-4419-9568-1 [contents] - 2010
- [j34]Patrick L. Combettes
Functions with prescribed best linear approximations. J. Approx. Theory 162(5): 1095-1116 (2010) - [j33]Hédy Attouch, Luis M. Briceño-Arias
A Parallel Splitting Method for Coupled Monotone Inclusions. SIAM J. Control. Optim. 48(5): 3246-3270 (2010) - [c35]Jérôme Bolte, Patrick L. Combettes
Alternating proximal algorithm for blind image recovery. ICIP 2010: 1673-1676 - [c34]Luis M. Briceño-Arias
Proximal method for geometry and texture image decomposition. ICIP 2010: 2721-2724
2000 – 2009
- 2009
- [c33]Patrick L. Combettes
Split convex minimization algorithm for signal recovery. ICASSP 2009: 685-688 - [r1]Patrick L. Combettes:
Fejér Monotonicity in Convex Optimization. Encyclopedia of Optimization 2009: 1016-1024 - 2007
- [j32]Patrick L. Combettes
A Douglas-Rachford Splitting Approach to Nonsmooth Convex Variational Signal Recovery. J. Sel. Topics Signal Processing 1(4): 564-574 (2007) - [j31]Patrick L. Combettes
Proximal Thresholding Algorithm for Minimization over Orthonormal Bases. SIAM J. Optim. 18(4): 1351-1376 (2007) - [c32]Patrick L. Combettes, Jean-Christophe Pesquet:
Sparse signal recovery by iterative proximal thresholding. EUSIPCO 2007: 1726-1730 - 2006
- [j30]Heinz H. Bauschke
A strongly convergent reflection method for finding the projection onto the intersection of two closed convex sets in a Hilbert space. J. Approx. Theory 141(1): 63-69 (2006) - [j29]Heinz H. Bauschke
Extrapolation algorithm for affine-convex feasibility problems. Numer. Algorithms 41(3): 239-274 (2006) - [c31]Caroline Chaux, Patrick L. Combettes, Jean-Christophe Pesquet, Valérie R. Wajs:
Iterative image deconvolution using overcomplete representations. EUSIPCO 2006: 1-5 - [c30]Heinz H. Bauschke, Patrick L. Combettes
A Decomposition Method for Nonsmooth Convex Variational Signal Recovery. ICASSP (5) 2006: 989-992 - 2005
- [j28]Thomas D. Capricelli, Patrick L. Combettes
Parallel Block-Iterative Reconstruction Algorithms for Binary Tomography. Electron. Notes Discret. Math. 20: 263-280 (2005) - [j27]Patrick L. Combettes
Signal Recovery by Proximal Forward-Backward Splitting. Multiscale Model. Simul. 4(4): 1168-1200 (2005) - [c29]Heinz H. Bauschke
A new generation of iterative transform algorithms for phase contrast tomography. ICASSP (4) 2005: 89-92 - 2004
- [j26]Patrick L. Combettes
Wavelet-Constrained Image Restoration. Int. J. Wavelets Multiresolution Inf. Process. 2(4): 371-389 (2004) - [j25]Heinz H. Bauschke
Finding best approximation pairs relative to two closed convex sets in Hilbert spaces. J. Approx. Theory 127(2): 178-192 (2004) - [j24]Patrick L. Combettes
Proximal Methods for Cohypomonotone Operators. SIAM J. Control. Optim. 43(2): 731-742 (2004) - [j23]Patrick L. Combettes
Image restoration subject to a total variation constraint. IEEE Trans. Image Process. 13(9): 1213-1222 (2004) - [c28]Patrick L. Combettes
Constraint construction in convex set theoretic signal recovery via Stein's principle [image denoising example]. ICASSP (2) 2004: 813-816 - [c27]Patrick L. Combettes
Estimating first-order finite-difference information in image restoration problems. ICIP 2004: 321-324 - [c26]Patrick L. Combettes
Theoretical analysis of some regularized image denoising methods. ICIP 2004: 969-972 - 2003
- [j22]Heinz H. Bauschke
Bregman Monotone Optimization Algorithms. SIAM J. Control. Optim. 42(2): 596-636 (2003) - [j21]Heinz H. Bauschke
Iterating Bregman Retractions. SIAM J. Optim. 13(4): 1159-1173 (2003) - [j20]Patrick L. Combettes
A block-iterative surrogate constraint splitting method for quadratic signal recovery. IEEE Trans. Signal Process. 51(7): 1771-1782 (2003) - [c25]Patrick L. Combettes
Total variation information in image recovery. ICIP (3) 2003: 373-376 - [c24]Patrick L. Combettes
Image deconvolution with total variation bounds. ISSPA (1) 2003: 441-444 - 2002
- [j19]Patrick L. Combettes
An adaptive level set method for nondifferentiable constrained image recovery. IEEE Trans. Image Process. 11(11): 1295-1304 (2002) - [c23]Heinz H. Bauschke, Patrick L. Combettes
On the structure of some phase retrieval algorithms. ICIP (2) 2002: 841-844 - 2001
- [j18]Heinz H. Bauschke
A Weak-to-Strong Convergence Principle for Fejé-Monotone Methods in Hilbert Spaces. Math. Oper. Res. 26(2): 248-264 (2001) - [j17]Patrick L. Combettes
On the numerical robustness of the parallel projection method in signal synthesis. IEEE Signal Process. Lett. 8(2): 45-47 (2001) - [c22]Patrick L. Combettes
Convex set theoretic image recovery with inexact projection algorithms. ICIP (1) 2001: 257-260 - 2000
- [j16]Patrick L. Combettes
Strong Convergence of Block-Iterative Outer Approximation Methods for Convex Optimization. SIAM J. Control. Optim. 38(2): 538-565 (2000) - [c21]Patrick L. Combettes
A parallel constraint disintegration and approximation scheme for quadratic signal recovery. ICASSP 2000: 165-168 - [c20]Jian Luo, Patrick L. Combettes
A level-set subgradient projection algorithm for non-differentiable signal restoration with multiple constraints. ICASSP 2000: 225-228
1990 – 1999
- 1999
- [j15]Patrick L. Combettes
Hard-constrained inconsistent signal feasibility problems. IEEE Trans. Signal Process. 47(9): 2460-2468 (1999) - [c19]Jian Luo, Patrick L. Combettes:
A subgradient projection algorithm for nondifferentiable signal recovery. NSIP 1999: 452-456 - 1998
- [j14]Patrick L. Combettes
Convex Multiresolution Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20(12): 1308-1318 (1998) - [c18]Patrick L. Combettes, P. Boudon:
Constrained pulse shape synthesis for digital communications. EUSIPCO 1998: 1-4 - [c17]Patrick L. Combettes
A block-iterative quadratic signal recovery algorithm. ICASSP 1998: 2917-2920 - [c16]Patrick L. Combettes
Nonlinear Multiresolution Image Analysis via Convex Projections. ICIP (2) 1998: 762-765 - 1997
- [j13]Patrick L. Combettes
Convex set theoretic image recovery by extrapolated iterations of parallel subgradient projections. IEEE Trans. Image Process. 6(4): 493-506 (1997) - [c15]Patrick L. Combettes
Hard-constrained signal feasibility problems. ICASSP 1997: 2569-2572 - 1996
- [j12]Patrick L. Combettes
Combining statistical information in set theoretic estimation. IEEE Signal Process. Lett. 3(3): 61-62 (1996) - [j11]Jean-Christophe Pesquet, Patrick L. Combettes
Wavelet synthesis by alternating projections. IEEE Trans. Signal Process. 44(3): 728-732 (1996) - [c14]Hong Puh, Patrick L. Combettes
Operator theoretic image coding. ICASSP 1996: 1862-1865 - [c13]Patrick L. Combettes
Generalized convex set theoretic image recovery. ICIP (2) 1996: 453-456 - 1995
- [j10]Pascal Bondon
Volterra filtering and higher order whiteness. IEEE Trans. Signal Process. 43(9): 2209-2212 (1995) - [c12]Patrick L. Combettes
Adaptive linear filtering with convex constraints. ICASSP 1995: 1372-1375 - [c11]Patrick L. Combettes
Constrained image recovery in a product space. ICIP 1995: 25-28 - 1994
- [j9]Patrick L. Combettes
Inconsistent signal feasibility problems: least-squares solutions in a product space. IEEE Trans. Signal Process. 42(11): 2955-2966 (1994) - [c10]Patrick L. Combettes
A fast parallel projection algorithm for set theoretic image recovery. ICASSP (5) 1994: 473-476 - [c9]Patrick L. Combettes
Convex Set Theoretic Image Recovery via Chaotic Iterations of Approximate Projections. ICIP (3) 1994: 182-186 - 1993
- [j8]Patrick L. Combettes
The foundations of set theoretic estimation. Proc. IEEE 81(2): 182-208 (1993) - [j7]Patrick L. Combettes
Signal recovery by best feasible approximation. IEEE Trans. Image Process. 2(2): 269-271 (1993) - [c8]Pascal Bondon, Patrick L. Combettes
Volterra prediction models and higher order whiteness. ICASSP (4) 1993: 212-215 - [c7]Patrick L. Combettes
Parallel projection methods for set theoretic signal reconstruction and restoration. ICASSP (5) 1993: 297-300 - 1992
- [j6]Patrick L. Combettes
Convex set theoretic image recovery: History, current status, and new directions. J. Vis. Commun. Image Represent. 3(4): 307-315 (1992) - [j5]Jack W. Silverstein
Signal detection via spectral theory of large dimensional random matrices. IEEE Trans. Signal Process. 40(8): 2100-2105 (1992) - [j4]Patrick L. Combettes
Best stable and invertible approximations for ARMA systems. IEEE Trans. Signal Process. 40(12): 3066-3069 (1992) - [c6]Patrick L. Combettes
A general framework for the incorporation of uncertainty in set theoretic estimation. ICASSP 1992: 349-352 - 1991
- [j3]Patrick L. Combettes
The use of noise properties in set theoretic estimation. IEEE Trans. Signal Process. 39(7): 1630-1641 (1991) - [j2]Patrick L. Combettes
Set theoretic estimation by random search. IEEE Trans. Signal Process. 39(7): 1669-1671 (1991) - [c5]Patrick L. Combettes
The foundations of set theoretic estimation. ICASSP 1991: 2921-2924 - 1990
- [c4]Patrick L. Combettes
New methods for the synthesis of set theoretic estimates [digital signal processing]. ICASSP 1990: 2531-2534
1980 – 1989
- 1989
- [j1]Patrick L. Combettes
Methods for digital restoration of signals degraded by a stochastic impulse response. IEEE Trans. Acoust. Speech Signal Process. 37(3): 393-401 (1989) - [c3]Patrick L. Combettes
General order moments in set theoretic estimation. ICASSP 1989: 2101-2104 - 1988
- [c2]Patrick L. Combettes
Stability of the linear prediction filter: a set theoretic approach. ICASSP 1988: 2288-2291 - 1987
- [c1]H. Joel Trussell, Patrick L. Combettes
Considerations for the restoration of stochastic degradations. ICASSP 1987: 1209-1212
Coauthor Index
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