On the public citation graph

Projection onto an acute cone and convex feasibility problem

https://doi.org/10.1007/bfb0035467
0 signed · 27 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/bf01389537openalex-snapshot
Convergence results for an accelerated nonlinear cimmino algorithm
inferredcites →https://doi.org/10.1007/bf02017349openalex-snapshot
Relaxed outer projections, weighted averages and convex feasibility
inferredcites →https://doi.org/10.1007/bf02612715openalex-snapshot
Decomposition through formalization in a product space
inferredcites →https://doi.org/10.1016/0024-3795(89)90375-3openalex-snapshot
Block-iterative projection methods for parallel computation of solutions to convex feasibility problems
inferredcites →https://doi.org/10.1016/0041-5553(67)90040-7openalex-snapshot
The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming
inferredcites →https://doi.org/10.1016/0041-5553(67)90113-9openalex-snapshot
The method of projections for finding the common point of convex sets
inferredcites →https://doi.org/10.1016/0041-5553(69)90061-5openalex-snapshot
Minimization of unsmooth functionals
inferredcites →https://doi.org/10.1080/00207169008803865openalex-snapshot
On the behavior of a block-iterative projection method for solving convex feasibility problems
inferredcites →https://doi.org/10.1080/02331939108843731openalex-snapshot
A general iterative scheme with applications to convex optimization and related fields
inferredcites →https://doi.org/10.1287/moor.5.3.388openalex-snapshot
The Relaxation Method for Solving Systems of Linear Inequalities
inferredcites →https://doi.org/10.4153/cjm-1954-037-2openalex-snapshot
The Relaxation Method for Linear Inequalities

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-642-30901-4_1openalex-snapshot
Introduction
inferred← citeshttps://doi.org/10.1007/978-3-642-30901-4_2openalex-snapshot
Algorithmic Operators
inferred← citeshttps://doi.org/10.1007/978-3-642-30901-4_3openalex-snapshot
Convergence of Iterative Methods
inferred← citeshttps://doi.org/10.1007/978-3-642-30901-4_4openalex-snapshot
Algorithmic Projection Operators
inferred← citeshttps://doi.org/10.1007/978-3-642-30901-4_5openalex-snapshot
Projection Methods
inferred← citeshttps://doi.org/10.1007/978-3-642-58891-4_9openalex-snapshot
Convergent Stepsize Rules for Subgradient Optimization
inferred← citeshttps://doi.org/10.1007/978-3-642-80117-4_4openalex-snapshot
Variable Target Subgradient Method of Projection onto an Acute Cone in Convex Minimization
inferred← citeshttps://doi.org/10.1007/bf02192226openalex-snapshot
Geometrically convergent projection method in matrix games
inferred← citeshttps://doi.org/10.1007/s101070050068openalex-snapshot
A method of projection onto an acute cone with level control in convex minimization
inferred← citeshttps://doi.org/10.1016/s0024-3795(01)00284-1openalex-snapshot
Obtuse cones and Gram matrices with nonnegative inverse
inferred← citeshttps://doi.org/10.1016/s0167-6377(98)00003-0openalex-snapshot
A superlinearly convergent projection algorithm for solving the convex inequality problem
inferred← citeshttps://doi.org/10.1023/b:jota.0000025708.31430.22openalex-snapshot
Reflection-Projection Method for Convex Feasibility Problems with an Obtuse Cone
inferred← citeshttps://doi.org/10.1080/0233193031000079883openalex-snapshot
Residual Selection in A Projection Method for Convex Minimization Problems
inferred← citeshttps://doi.org/10.1287/moor.24.1.237openalex-snapshot
The Efficiency of Ballstep Subgradient Level Methods for Convex Optimization
inferred← citeshttps://doi.org/10.7151/dmdico.1034openalex-snapshot
Selection strategies in projection methods for convex minimization problems
inferred← citeshttps://doi.org/10.7151/dmdico.1075openalex-snapshot
Projection method with residual selection for linear feasibility problems
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.