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Massimo Fornasier
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- affiliation: Technical University Munich, Germany
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2020 – today
- 2024
- [j32]Massimo Fornasier, Timo Klock, Konstantin Riedl:
Consensus-Based Optimization Methods Converge Globally. SIAM J. Optim. 34(3): 2973-3004 (2024) - [i16]Chinmay Datar, Taniya Kapoor, Abhishek Chandra, Qing Sun, Iryna Burak, Erik Lien Bolager, Anna Veselovska, Massimo Fornasier, Felix Dietrich:
Solving partial differential equations with sampled neural networks. CoRR abs/2405.20836 (2024) - 2023
- [i15]Konstantin Riedl, Timo Klock, Carina Geldhauser, Massimo Fornasier:
Gradient is All You Need? CoRR abs/2306.09778 (2023) - [i14]Cristina Cipriani, Massimo Fornasier, Alessandro Scagliotti:
From NeurODEs to AutoencODEs: a mean-field control framework for width-varying Neural Networks. CoRR abs/2307.02279 (2023) - [i13]Massimo Fornasier, Pascal Heid, Giacomo Enrico Sodini:
Approximation Theory, Computing, and Deep Learning on the Wasserstein Space. CoRR abs/2310.19548 (2023) - 2022
- [j31]Massimo Fornasier, Hui Huang, Lorenzo Pareschi, Philippe Sünnen:
Anisotropic Diffusion in Consensus-Based Optimization on the Sphere. SIAM J. Optim. 32(3): 1984-2012 (2022) - [c7]Massimo Fornasier, Timo Klock, Konstantin Riedl:
Convergence of Anisotropic Consensus-Based Optimization in Mean-Field Law. EvoApplications 2022: 738-754 - [i12]Massimo Fornasier, Timo Klock, Marco Mondelli, Michael Rauchensteiner:
Finite Sample Identification of Wide Shallow Neural Networks with Biases. CoRR abs/2211.04589 (2022) - 2021
- [j30]Massimo Fornasier, Johannes Maly, Valeriya Naumova:
Robust recovery of low-rank matrices with non-orthogonal sparse decomposition from incomplete measurements. Appl. Math. Comput. 392: 125702 (2021) - [j29]Massimo Fornasier, Lorenzo Pareschi, Hui Huang, Philippe Sünnen:
Consensus-Based Optimization on the Sphere: Convergence to Global Minimizers and Machine Learning. J. Mach. Learn. Res. 22: 237:1-237:55 (2021) - [i11]Christian Fiedler, Massimo Fornasier, Timo Klock, Michael Rauchensteiner:
Stable Recovery of Entangled Weights: Towards Robust Identification of Deep Neural Networks from Minimal Samples. CoRR abs/2101.07150 (2021) - [i10]Massimo Fornasier, Timo Klock, Konstantin Riedl:
Consensus-based optimization methods converge globally in mean-field law. CoRR abs/2103.15130 (2021) - [i9]Massimo Fornasier, Timo Klock, Konstantin Riedl:
Convergence of Anisotropic Consensus-Based Optimization in Mean-Field Law. CoRR abs/2111.08136 (2021) - 2020
- [j28]Lars Diening, Massimo Fornasier, Roland Tomasi, Maximilian Wank:
A Relaxed Kačanov iteration for the p-poisson problem. Numerische Mathematik 145(1): 1-34 (2020) - [i8]Massimo Fornasier, Hui Huang, Lorenzo Pareschi, Philippe Sünnen:
Consensus-based Optimization on the Sphere II: Convergence to Global Minimizers and Machine Learning. CoRR abs/2001.11988 (2020) - [i7]Massimo Fornasier, Hui Huang, Lorenzo Pareschi, Philippe Sünnen:
Consensus-Based Optimization on the Sphere I: Well-Posedness and Mean-Field Limit. CoRR abs/2001.11994 (2020)
2010 – 2019
- 2019
- [i6]Massimo Fornasier, Timo Klock, Michael Rauchensteiner:
Robust and Resource Efficient Identification of Two Hidden Layer Neural Networks. CoRR abs/1907.00485 (2019) - [i5]Stefano Almi, Massimo Fornasier, Richard Huber:
Data-driven Evolutions of Critical Points. CoRR abs/1911.00298 (2019) - 2018
- [i4]Massimo Fornasier, Jan Vybíral, Ingrid Daubechies:
Identification of Shallow Neural Networks by Fewest Samples. CoRR abs/1804.01592 (2018) - 2017
- [j27]Mattia Bongini, Massimo Fornasier, Francesco Rossi, Francesco Solombrino:
Mean-Field Pontryagin Maximum Principle. J. Optim. Theory Appl. 175(1): 1-38 (2017) - 2016
- [j26]Massimo Fornasier, Steffen Peter, Holger Rauhut, Stephan Worm:
Conjugate gradient acceleration of iteratively re-weighted least squares methods. Comput. Optim. Appl. 65(1): 205-259 (2016) - 2015
- [j25]Mattia Bongini, Massimo Fornasier, Oliver Junge, Benjamin Scharf:
Sparse control of alignment models in high dimension. Networks Heterog. Media 10(3): 647-697 (2015) - [j24]Marco Artina, Massimo Fornasier, Stefano Micheletti, Simona Perotto:
Anisotropic Mesh Adaptation for Crack Detection In Brittle Materials. SIAM J. Sci. Comput. 37(4) (2015) - [j23]Steffen Peter, Marco Artina, Massimo Fornasier:
Damping Noise-Folding and Enhanced Support Recovery in Compressed Sensing. IEEE Trans. Signal Process. 63(22): 5990-6002 (2015) - [r1]Massimo Fornasier, Holger Rauhut:
Compressive Sensing. Handbook of Mathematical Methods in Imaging 2015: 205-256 - 2014
- [j22]Martin Ehler, Massimo Fornasier, Juliane Sigl:
Quasi-linear Compressed Sensing. Multiscale Model. Simul. 12(2): 725-754 (2014) - [j21]Mattia Bongini, Massimo Fornasier:
Sparse stabilization of dynamical systems driven by attraction and avoidance forces. Networks Heterog. Media 9(1): 1-31 (2014) - [j20]Marco Di Francesco, Massimo Fornasier, Jan-Christian Hütter, Daniel Matthes:
Asymptotic Behavior of Gradient Flows Driven by Nonlocal Power Repulsion and Attraction Potentials in One Dimension. SIAM J. Math. Anal. 46(6): 3814-3837 (2014) - [j19]Massimo Fornasier, Valeriya Naumova, Sergei V. Pereverzyev:
Parameter Choice Strategies for Multipenalty Regularization. SIAM J. Numer. Anal. 52(4): 1770-1794 (2014) - [c6]Massimo Fornasier, Benedetto Piccoli, Nastassia Pouradier Duteil, Francesco Rossi:
Mean-field optimal control by leaders. CDC 2014: 6957-6962 - [c5]Mattia Bongini, Massimo Fornasier, Fabian Frcohlich, Laleh Haghverdi:
Sparse control of force field dynamics. NetGCooP 2014: 195-200 - 2013
- [j18]Marco Artina, Massimo Fornasier, Francesco Solombrino:
Linearly Constrained Nonsmooth and Nonconvex Minimization. SIAM J. Optim. 23(3): 1904-1937 (2013) - [c4]Marco Artina, Massimo Fornasier, Stefano Micheletti, Simona Perotto:
Anisotropic Adaptive Meshes for Brittle Fractures: Parameter Sensitivity. ENUMATH 2013: 293-301 - [i3]Marco Artina, Massimo Fornasier, Steffen Peter:
Damping Noise-Folding and Enhanced Support Recovery in Compressed Sensing. CoRR abs/1307.5725 (2013) - [i2]Martin Ehler, Massimo Fornasier, Juliane Sigl:
Quasi-Linear Compressed Sensing. CoRR abs/1311.1642 (2013) - 2012
- [j17]Massimo Fornasier, Karin Schnass, Jan Vybíral:
Learning Functions of Few Arbitrary Linear Parameters in High Dimensions. Found. Comput. Math. 12(2): 229-262 (2012) - [j16]Stephan Dahlke, Massimo Fornasier, Thorsten Raasch:
Multilevel preconditioning and adaptive sparse solution of inverse problems. Math. Comput. 81(277): 419-446 (2012) - [j15]Massimo Fornasier, Yunho Kim, Andreas Langer, Carola-Bibiane Schönlieb:
Wavelet Decomposition Method for L2//TV-Image Deblurring. SIAM J. Imaging Sci. 5(3): 857-885 (2012) - 2011
- [j14]Massimo Fornasier, Jan Haskovec, Jan Vybíral:
Particle Systems and Kinetic Equations Modeling Interacting Agents in High Dimension. Multiscale Model. Simul. 9(4): 1727-1764 (2011) - [j13]Massimo Fornasier, Holger Rauhut, Rachel A. Ward:
Low-rank Matrix Recovery via Iteratively Reweighted Least Squares Minimization. SIAM J. Optim. 21(4): 1614-1640 (2011) - 2010
- [b1]Massimo Fornasier:
Theoretical Foundations and Numerical Methods for Sparse Recovery. Radon Series on Computational and Applied Mathematics 9, de Gruyter 2010, ISBN 978-3-11-022614-0, pp. I-X, 1-340 - [j12]Massimo Fornasier, Rachel A. Ward:
Iterative Thresholding Meets Free-Discontinuity Problems. Found. Comput. Math. 10(5): 527-567 (2010) - [j11]Stephan Dahlke, Massimo Fornasier, Karlheinz Gröchenig:
Optimal adaptive computations in the Jaffard algebra and localized frames. J. Approx. Theory 162(1): 153-185 (2010) - [j10]Massimo Fornasier, Andreas Langer, Carola-Bibiane Schönlieb:
A convergent overlapping domain decomposition method for total variation minimization. Numerische Mathematik 116(4): 645-685 (2010) - [i1]Massimo Fornasier, Karin Schnass, Jan Vybíral:
Learning Functions of Few Arbitrary Linear Parameters in High Dimensions. CoRR abs/1008.3043 (2010)
2000 – 2009
- 2009
- [j9]Massimo Fornasier, Ronny Ramlau, Gerd Teschke:
The application of joint sparsity and total variation minimization algorithms to a real-life art restoration problem. Adv. Comput. Math. 31(1-3): 157-184 (2009) - [j8]Massimo Fornasier, Carola-Bibiane Schönlieb:
Subspace Correction Methods for Total Variation and 1-Minimization. SIAM J. Numer. Anal. 47(5): 3397-3428 (2009) - [c3]Massimo Fornasier:
Compressive Algorithms-Adaptive Solutions of PDEs and Variational Problems. IMA Conference on the Mathematics of Surfaces 2009: 143-169 - 2008
- [j7]Maria Charina, Costanza Conti, Massimo Fornasier:
Adaptive frame methods for nonlinear variational problems. Numerische Mathematik 109(1): 45-75 (2008) - [j6]Massimo Fornasier, Holger Rauhut:
Recovery Algorithms for Vector-Valued Data with Joint Sparsity Constraints. SIAM J. Numer. Anal. 46(2): 577-613 (2008) - [c2]Ingrid Daubechies, Ronald A. DeVore, Massimo Fornasier, C. Sinan Güntürk:
Iteratively Re-weighted Least Squares minimization: Proof of faster than linear rate for sparse recovery. CISS 2008: 26-29 - 2007
- [j5]Stephan Dahlke, Massimo Fornasier, Thorsten Raasch:
Adaptive frame methods for elliptic operator equations. Adv. Comput. Math. 27(1): 27-63 (2007) - [j4]Massimo Fornasier, Riccardo March:
Restoration of Color Images by Vector Valued BV Functions and Variational Calculus. SIAM J. Appl. Math. 68(2): 437-460 (2007) - [c1]Massimo Fornasier:
Faithful Recovery of Vector Valued Functions from Incomplete Data. SSVM 2007: 116-127 - 2006
- [j3]Massimo Fornasier:
Nonlinear Projection Recovery in Digital Inpainting for Color Image Restoration. J. Math. Imaging Vis. 24(3): 359-373 (2006) - 2005
- [j2]Maria Morandi Cecchi, Massimo Fornasier:
Fast homogenization algorithm based on asymptotic theory and multiscale schemes. Numer. Algorithms 40(2): 171-186 (2005) - [j1]Massimo Fornasier, Domenico Toniolo:
Fast, robust and efficient 2D pattern recognition for re-assembling fragmented images. Pattern Recognit. 38(11): 2074-2087 (2005)
Coauthor Index
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last updated on 2024-10-07 21:24 CEST by the dblp team
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