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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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Papers overview

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2018
2018
Stochastic convex optimization algorithms are the most popular way to train machine learning models on large-scale data. Scaling… 
2016
2016
We propose a new framework for black-box convex optimization which is well-suited for situations where gradient computations are… 
2013
2013
In this paper we present an $\tilde{O}(m\sqrt{n}\log^{O(1)}U)$ time algorithm for solving the maximum flow problem on directed… 
2013
2013
Nonlinear rescaling is a tool for solving large-scale nonlinear programming problems. The primal-dual nonlinear rescaling method… 
2009
2009
The notion of self-concordant function on Euclidean spaces was introduced and studied by Nesterov and Nemirovsky (6). They have… 
2004
2004
In this paper we study special barrier functions for convex cones, which are the sum of a self- concordant barrier for the cone… 
2001
2001
Abstract.The geometric mean and the function (det(·))1/m (on the m-by-m positive definite matrices) are examples of “hyperbolic… 
1999
1999
The geometric mean and the function (det( )) (on the mby-m positive de nite matrices) are examples of \hyperbolic means… 
1999
1999
This paper presents an algorithm for solving multi-stage stochastic nonlinear programs. The algorithm is based on the Lagrangian… 
1998
1998
In this paper first we prove four fundamental theorems of the alternative, called scaling dualities, characterizing exact and…