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- Massimo Fornasier

Discipline name
D-index
D-index (Discipline H-index) only includes papers and citation values for an examined
discipline in contrast to General H-index which accounts for publications across all
disciplines.
Citations
Publications
World Ranking
National Ranking

Mathematics
D-index
37
Citations
7,612
114
World Ranking
1656
National Ranking
94

Engineering and Technology
D-index
34
Citations
6,729
105
World Ranking
5582
National Ranking
194

- Mathematical analysis
- Algebra
- Artificial intelligence

His main research concerns Mathematical optimization, Numerical analysis, Norm, Inverse problem and Landweber iteration. His work in the fields of Mathematical optimization, such as Optimal control, overlaps with other areas such as Eight-point algorithm. He interconnects Theoretical computer science, Domain decomposition methods, Banach space, Elliptic operator and Discretization in the investigation of issues within Numerical analysis.

His work carried out in the field of Norm brings together such families of science as Sparse matrix, Hyperplane, Combinatorics and Ode. Massimo Fornasier has included themes like Value and Algorithm, Artificial intelligence, Compressed sensing in his Inverse problem study. The various areas that he examines in his Landweber iteration study include Nonlinear conjugate gradient method, Proximal Gradient Methods, Gradient descent and Numerical linear algebra.

- Iteratively re-weighted least squares minimization for sparse recovery (954 citations)
- Asymptotic Flocking Dynamics for the Kinetic Cucker–Smale Model (366 citations)
- Accelerated Projected Gradient Method for Linear Inverse Problems with Sparsity Constraints (244 citations)

Massimo Fornasier mainly focuses on Applied mathematics, Mathematical optimization, Algorithm, Mathematical analysis and Compressed sensing. His Optimal control and Iterative method investigations are all subjects of Mathematical optimization research. His Algorithm research includes themes of Domain decomposition methods, Inverse problem, Minification, Inpainting and Numerical analysis.

His Inverse problem research integrates issues from Iterative thresholding, Thresholding, Norm and Regularization. His biological study deals with issues like Wavelet, which deal with fields such as Interpretation, Limiting case and Dilation. His work investigates the relationship between Compressed sensing and topics such as Matrix that intersect with problems in Combinatorics.

- Applied mathematics (29.53%)
- Mathematical optimization (21.48%)
- Algorithm (19.46%)

- Applied mathematics (29.53%)
- Matrix (8.05%)
- Limit (10.07%)

His primary areas of investigation include Applied mathematics, Matrix, Limit, Probability distribution and Sequence. His Applied mathematics research incorporates themes from Banach space, State space, Uniqueness, Critical point and Elastic energy. He does research in Matrix, focusing on Restricted isometry property specifically.

His Limit research is multidisciplinary, relying on both Function, Convex combination and Global optimization. His Convex combination research incorporates elements of Numerical analysis and Asymptotic analysis. His Sequence study combines topics in areas such as Connection, Order and Tensor product.

- Mean-field optimal control as Gamma-limit of finite agent controls (18 citations)
- Consensus-based Optimization on the Sphere II: Convergence to Global Minimizers and Machine Learning. (14 citations)
- A Relaxed Kačanov iteration for the p -poisson problem (11 citations)

- Mathematical analysis
- Algebra
- Geometry

The scientist’s investigation covers issues in Applied mathematics, Subspace topology, Sequence, Global optimization and Probability distribution. He performs multidisciplinary study in Applied mathematics and Replicator equation in his work. The study incorporates disciplines such as Type, Minimax approximation algorithm, Homogeneous space, Gradient descent and Nonlinear system in addition to Subspace topology.

His Sequence research focuses on Weak solution and how it connects with Numerical analysis. The Numerical analysis study combines topics in areas such as Function, Artificial intelligence and Asymptotic analysis. His Global optimization research includes elements of Mean field limit, Machine learning, Differential, Well posedness and Convex combination.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Iteratively reweighted least squares minimization for sparse recovery

Ingrid Daubechies;Ronald DeVore;Massimo Fornasier;C. Si̇nan Güntürk.

Communications on Pure and Applied Mathematics **(2008)**

1338 Citations

Iteratively re-weighted least squares minimization for sparse recovery

Ingrid Daubechies;Ronald DeVore;Massimo Fornasier;C. Sinan Gunturk.

arXiv: Numerical Analysis **(2008)**

1035 Citations

Asymptotic Flocking Dynamics for the Kinetic Cucker–Smale Model

José A. Carrillo;M. Fornasier;Jesús Rosado;Giuseppe Toscani.

Siam Journal on Mathematical Analysis **(2010)**

442 Citations

Particle, kinetic, and hydrodynamic models of swarming

José A. Carrillo;Massimo Fornasier;Giuseppe Toscani;Francesco Vecil.

**(2010)**

352 Citations

Accelerated Projected Gradient Method for Linear Inverse Problems with Sparsity Constraints

Ingrid Daubechies;Massimo Fornasier;Ignace Loris.

Journal of Fourier Analysis and Applications **(2008)**

339 Citations

Recovery Algorithms for Vector-Valued Data with Joint Sparsity Constraints

Massimo Fornasier;Holger Rauhut.

SIAM Journal on Numerical Analysis **(2008)**

258 Citations

Iterative thresholding algorithms

Massimo Fornasier;Holger Rauhut.

Applied and Computational Harmonic Analysis **(2008)**

238 Citations

Low-rank Matrix Recovery via Iteratively Reweighted Least Squares Minimization

Massimo Fornasier;Holger Rauhut;Rachel Ward.

Siam Journal on Optimization **(2011)**

234 Citations

Quasi-orthogonal decompositions of structured frames

Massimo Fornasier.

Journal of Mathematical Analysis and Applications **(2004)**

181 Citations

Continuous Frames, Function Spaces, and the Discretization Problem

Massimo Fornasier;Holger Rauhut.

Journal of Fourier Analysis and Applications **(2005)**

175 Citations

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