Yair Censor

Bio-sketch and research interests appear at: http://math.haifa.ac.il/YAIR/censor-interests.html

Sparsity constrained split feasibility for dose-volume constraints in inverse planning of intensity-modulated photon or proton therapy

  • Mark Brooke
  • Margherita Casiraghi
  • Yair Censor
  • Scott Penfold
  • Reinhard W. Schulte
  • Rafal Zalas
    • Categories Biomedical Applications, Convex Optimization Tags , , , , , ,

    A split feasibility formulation for the inverse problem of intensity-modulated radiation therapy (IMRT) treatment planning with dose-volume constraints (DVCs) included in the planning algorithm is presented. It involves a new type of sparsity constraint that enables the inclusion of a percentage-violation constraint in the model problem and its handling by continuous (as opposed to integer) … Read more

    Can linear superiorization be useful for linear optimization problems?

  • Yair Censor
    • Categories Constrained Nonlinear Optimization, Linear Programming, Problem Solving Environments Tags , , , , , , , , ,

    Linear superiorization considers linear programming problems but instead of attempting to solve them with linear optimization methods it employs perturbation resilient feasibility-seeking algorithms and steers them toward reduced (not necessarily minimal) target function values. The two questions that we set out to explore experimentally are (i) Does linear superiorization provide a feasible point whose linear … Read more

    Linear superiorization for infeasible linear programming

  • Yair Censor
  • Yehuda Zur
    • Categories Constrained Nonlinear Optimization, Linear Programming

    Linear superiorization (abbreviated: LinSup) considers linear programming (LP) problems wherein the constraints as well as the objective function are linear. It allows to steer the iterates of a feasibility-seeking iterative process toward feasible points that have lower (not necessarily minimal) values of the objective function than points that would have been reached by the same … Read more

    The implicit convex feasibility problem and its application to adaptive image denoising

  • Yair Censor
  • Aviv Gibali
  • Frank Lenzen
  • Christoph Schnörr
    • Categories Biomedical Applications, Convex and Nonsmooth Optimization Tags , , , , ,

    The implicit convex feasibility problem attempts to find a point in the intersection of a finite family of convex sets, some of which are not explicitly determined but may vary. We develop simultaneous and sequential projection methods capable of handling such problems and demonstrate their applicability to image denoising in a specific medical imaging situation. … Read more

    New Douglas-Rachford algorithmic structures and their convergence analyses

  • Yair Censor
  • Rafiq Mansour
    • Categories Convex Optimization Tags , ,

    In this paper we study new algorithmic structures with Douglas- Rachford (DR) operators to solve convex feasibility problems. We propose to embed the basic two-set-DR algorithmic operator into the String-Averaging Projections (SAP) and into the Block-Iterative Pro- jection (BIP) algorithmic structures, thereby creating new DR algo- rithmic schemes that include the recently proposed cyclic Douglas- … Read more

    Techniques in Iterative Proton CT Image Reconstruction

  • Yair Censor
  • Scott Penfold
    • Categories Biomedical Applications, Convex Optimization Tags , , , , , ,

    This is a review paper on some of the physics, modeling, and iterative algorithms in proton computed tomography (pCT) image reconstruction. The primary challenge in pCT image reconstruction lies in the degraded spatial resolution resulting from multiple Coulomb scattering within the imaged object. Analytical models such as the most likely path (MLP) have been proposed … Read more

    Bounded perturbation resilience of projected scaled gradient methods

  • Yair Censor
  • Ming Jiang
  • Wenma Jin
    • Categories Constrained Nonlinear Optimization, Convex Optimization Tags , , ,

    We investigate projected scaled gradient (PSG) methods for convex minimization problems. These methods perform a descent step along a diagonally scaled gradient direction followed by a feasibility regaining step via orthogonal projection onto the constraint set. This constitutes a generalized algorithmic structure that encompasses as special cases the gradient projection method, the projected Newton method, … Read more

    Weak and Strong Superiorization: Between Feasibility-Seeking and Minimization

  • Yair Censor
    • Categories Constrained Nonlinear Optimization, Convex Optimization

    We review the superiorization methodology, which can be thought of, in some cases, as lying between feasibility-seeking and constrained minimization. It is not quite trying to solve the full fledged constrained minimization problem; rather, the task is to find a feasible point which is superior (with respect to an objective function value) to one returned … Read more

    Projection Methods: An Annotated Bibliography of Books and Reviews

  • Andrzej Cegielski
  • Yair Censor
    • Categories Constrained Nonlinear Optimization, Convex and Nonsmooth Optimization Tags , ,

    Projections onto sets are used in a wide variety of methods in optimization theory but not every method that uses projections really belongs to the class of projection methods as we mean it here. Here projection methods are iterative algorithms that use projections onto sets while relying on the general principle that when a family … Read more

    Strict Fejér Monotonicity by Superiorization of Feasibility-Seeking Projection Methods

  • Yair Censor
  • Alexander J. Zaslavski
    • Categories Constrained Nonlinear Optimization, Parallel Algorithms Tags , , , , , , ,

    We consider the superiorization methodology, which can be thought of as lying between feasibility-seeking and constrained minimization. It is not quite trying to solve the full fledged constrained minimization problem; rather, the task is to find a feasible point which is superior (with respect to the objective function value) to one returned by a feasibility-seeking … Read more