References in zbMATH (referenced in 582 articles )

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  1. Benedetto, John J.; Li, Weilin: Super-resolution by means of Beurling minimal extrapolation (2020)
  2. Bettiol, Enrico; Létocart, Lucas; Rinaldi, Francesco; Traversi, Emiliano: A conjugate direction based simplicial decomposition framework for solving a specific class of dense convex quadratic programs (2020)
  3. Ciuperca, Gabriela; Maciak, Matúš: Changepoint detection by the quantile Lasso method (2020)
  4. Denoyelle, Quentin; Duval, Vincent; Peyré, Gabriel; Soubies, Emmanuel: The sliding Frank-Wolfe algorithm and its application to super-resolution microscopy (2020)
  5. Duarte, Roberto; Repetti, Audrey; Gómez, Pedro A.; Davies, Mike; Wiaux, Yves: Greedy approximate projection for magnetic resonance fingerprinting with partial volumes (2020)
  6. Luu, Tung Duy; Fadili, Jalal; Chesneau, Christophe: Sharp oracle inequalities for low-complexity priors (2020)
  7. Vogt, Michael: On the differences between (L_2) boosting and the Lasso (2020)
  8. Wang, Guoqiang; Wei, Xinyuan; Yu, Bo; Xu, Lijun: An efficient proximal block coordinate homotopy method for large-scale sparse least squares problems (2020)
  9. Zhao, Yun-Bin: Optimal (k)-thresholding algorithms for sparse optimization problems (2020)
  10. Aravkin, Aleksandr Y.; Burke, James V.; Drusvyatskiy, Dmitry; Friedlander, Michael P.; Roy, Scott: Level-set methods for convex optimization (2019)
  11. Barbara, Abdessamad; Jourani, Abderrahim; Vaiter, Samuel: Maximal solutions of sparse analysis regularization (2019)
  12. Becker, Ruben; Bonifaci, Vincenzo; Karrenbauer, Andreas; Kolev, Pavel; Mehlhorn, Kurt: Two results on slime mold computations (2019)
  13. Bi, Ning; Tan, Jun: Characterization of (\ell_1) minimizer in one-bit compressed sensing (2019)
  14. Carlsson, Marcus: On convex envelopes and regularization of non-convex functionals without moving global minima (2019)
  15. Charkhgard, Hadi; Eshragh, Ali: A new approach to select the best subset of predictors in linear regression modelling: bi-objective mixed integer linear programming (2019)
  16. Churchill, Victor; Gelb, Anne: Detecting edges from non-uniform Fourier data via sparse Bayesian learning (2019)
  17. Cui, Yiran; Morikuni, Keiichi; Tsuchiya, Takashi; Hayami, Ken: Implementation of interior-point methods for LP based on Krylov subspace iterative solvers with inner-iteration preconditioning (2019)
  18. Delon, Julie; Desolneux, Agnès; Sutour, Camille; Viano, Agathe: RNLp: mixing nonlocal and TV-Lp methods to remove impulse noise from images (2019)
  19. Dobbe, Roel; Liu, Stephan; Yuan, Ye; Tomlin, Claire: Blind identification of fully observed linear time-varying systems via sparse recovery (2019)
  20. Fan, Jianqing; Gong, Wenyan; Zhu, Ziwei: Generalized high-dimensional trace regression via nuclear norm regularization (2019)

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