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… (More)
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Papers overview

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2017
2017
We analyze the proximal Newton method for minimizing a sum of a self-concordant function and a convex function with an… (More)
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Highly Cited
2015
Highly Cited
2015
We propose a new distributed algorithm for empirical risk minimization in machine learning. The algorithm is based on an inexact… (More)
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2015
2015
We propose a variable metric framework for minimizing the sum of a self-concordant function and a possibly non-smooth convex… (More)
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2013
2013
The convex ℓ1-regularized log det divergence criterion has been shown to produce theoretically consistent graph learning. However… (More)
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Highly Cited
2009
Highly Cited
2009
Most of the non-asymptotic theoretical work in regression i s carried out for the square loss, where estimators can be obtained… (More)
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2009
2009
The notion of self-concordant function on Euclidean spaces was introduced and studied by Nesterov and Nemirovsky [6]. They have… (More)
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2006
2006
In this paper we develop a technique for constructing self-concordant barriers for convex cones. We start from a simple proof for… (More)
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2004
2004
This paper discusses self-concordant functions on smooth manifolds. In Euclidean space, this class of functions are utilized… (More)
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Highly Cited
1998
Highly Cited
1998
In this paper we continue the development of a theoretical foundation for efficient primal-dual interior-point algorithms for… (More)
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1997
1997
In this paper, we introduce the notion of a self-concordant convex-concave function, establish basic properties of these… (More)
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