Results 31 to 40 of about 27,291 (261)
Random projections for linear programming [PDF]
, 2017 Random projections are random linear maps, sampled from appropriate distributions, that approx- imately preserve certain geometrical invariants so that the approximation improves as the dimension of the space grows.
Liberti, Leo +2 more
core +4 more sources
Revisiting interval protection, a.k.a. partial cell suppression, for tabular data [PDF]
, 2016 The final publication is available at link.springer.comInterval protection or partial cell suppression was introduced in “M. Fischetti, J.-J. Salazar, Partial cell suppression: A new methodology for statistical disclosure control, Statistics and ...
Castro Pérez, Jordi +1 more
core +1 more source
A penalty barrier framework for nonconvex constrained optimization [PDF]
Journal of Nonsmooth Analysis and OptimizationWe consider minimization problems with structured objective function and smooth constraints, and present a flexible framework that combines the beneficial regularization effects of (exact) penalty and interior-point methods.
Alberto De Marchi, Andreas Themelis
doaj +1 more source
Exact duality in semidefinite programming based on elementary reformulations [PDF]
, 2015 In semidefinite programming (SDP), unlike in linear programming, Farkas' lemma may fail to prove infeasibility. Here we obtain an exact, short certificate of infeasibility in SDP by an elementary approach: we reformulate any semidefinite system of the ...
Liu, Minghui, Pataki, Gabor
core +3 more sources
Bad semidefinite programs: they all look the same [PDF]
, 2017 Conic linear programs, among them semidefinite programs, often behave pathologically: the optimal values of the primal and dual programs may differ, and may not be attained. We present a novel analysis of these pathological behaviors.
Bauschke H. +6 more
core +3 more sources
An Active Set Algorithm for Robust Combinatorial Optimization Based on Separation Oracles [PDF]
, 2018 We address combinatorial optimization problems with uncertain coefficients varying over ellipsoidal uncertainty sets. The robust counterpart of such a problem can be rewritten as a second-oder cone program (SOCP) with integrality constraints.
Buchheim, Christoph, De Santis, Marianna
core +2 more sources
A Still Simpler Way of Introducing the Interior-Point Method for Linear Programming
, 2015 Linear programming is now included in algorithm undergraduate and postgraduate courses for computer science majors. We give a self-contained treatment of an interior-point method which is particularly tailored to the typical mathematical background of CS
Mehlhorn, Kurt, Saxena, Sanjeev
core +1 more source
Advanced Functional Materials, EarlyView.This study presents novel anti‐counterfeiting tags with multilevel security features that utilize additional disguise features. They combine luminescent nanosized Ln‐MOFs with conductive polymers to multifunctional mixed‐matrix membranes and powder composites. The materials exhibit visible/NIR emission and matrix‐based conductivity even as black bodies.
Moritz Maxeiner +9 more
wiley +1 more source
Advanced Healthcare Materials, EarlyView.A miniaturized drug sensitivity and resistance testing (DSRT) workflow based on the Droplet Microarray (DMA) platform enables functional drug testing using minimal patient‐derived tumor material. By screening nanoliter‐scale droplets containing as few as 300 cells, this approach generates reproducible and tumor‐specific drug response profiles ...
Maryam Salarian +7 more
wiley +1 more source
Journal of Numerical Analysis and Approximation TheoryThe focus of this research is to apply primal-dual interior-point pathfollowing methods, specifically those derived from Newton’s method for solving convex quadratic semidefinite optimization (CQSDO) problems. In this paper, we present a numerical study
Yasmina Bendaas, Mohamed Achache
doaj +1 more source