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Self-concordant function

Known as: Self-concordant 
In optimization, a self-concordant function is a function for which A function is self-concordant if its restriction to any arbitrary line is self… 
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Related topics

Related topics

6 relations
Augmented Lagrangian methodBarrier functionInterior point methodList of numerical analysis topics

Broader (1)

Mathematical optimization

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses
In this paper, we study large-scale convex optimization algorithms based on the Newton method applied to regularized generalized… 
Highly Cited
2017
Highly Cited
2017
An homotopy method for $\ell_p$ regression provably beyond self-concordance and in input-sparsity time
We consider the problem of linear regression where the $\ell_2^n$ norm loss (i.e., the usual least squares loss) is replaced by… 
2015
2015
Matches between assigned goal-types and both implicit and explicit motive dispositions predict goal self-concordance
Abstract Some individuals feel strong conviction and interest in pursuing personal goals, and minimal pressure and compulsion (i… 
2009
2009
A class of self-concordant functions on Riemannian manifolds.
The notion of self-concordant function on Euclidean spaces was introduced and studied by Nesterov and Nemirovsky (6). They have… 
2008
2008
An Analytic Center Cutting Plane Approach for Conic Programming
We analyze the problem of finding a point strictly interior to a bounded, convex, and fully dimensional set from a finite… 
2006
2006
Constructing Self-Concordant Barriers for Convex Cones
In this paper we develop a technique for constructing self-concordant barriers for convex cones. We start from a simple proof for… 
Highly Cited
2004
Highly Cited
2004
Geometry of homogeneous convex cones, duality mapping, and optimal self-concordant barriers
Abstract.We study homogeneous convex cones. We first characterize the extreme rays of such cones in the context of their primal… 
Highly Cited
2002
Highly Cited
2002
On the Riemannian Geometry Defined by Self-Concordant Barriers and Interior-Point Methods
Abstract. We consider the Riemannian geometry defined on a convex set by the Hessian of a self-concordant barrier function, and… 
1999
1999
最適化アルゴリズムの新展開 : 内点法とその周辺VI Self-concordant 障壁関数による主内点法(II)
1998
1998
Primal-Dual Symmetry and Scale Invariance of Interior-Point Algorithms for Convex Optimization
We present a definition of symmetric primal-dual algorithms for convex optimization problems expressed in the conic form. After… 
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