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2019

2019

We study the smooth structure of convex functions by generalizing a powerful concept so-called self-concordance introduced by… Expand

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2015

Highly Cited

2015

We propose a new distributed algorithm for empirical risk minimization in machine learning. The algorithm is based on an inexact… Expand

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Highly Cited

2015

Highly Cited

2015

We propose a variable metric framework for minimizing the sum of a self-concordant function and a possibly non-smooth convex… Expand

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Highly Cited

2009

Highly Cited

2009

Most of the non-asymptotic theoretical work in regression is carried out for the square loss, where estimators can be obtained… Expand

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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… Expand

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2008

2008

We analyze the problem of finding a point strictly interior to a bounded, convex, and fully dimensional set from a finite… Expand

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Highly Cited

2003

Highly Cited

2003

We extend existing theories by linking transformational leadership to “self-concordance” at work. In two studies using diverse… Expand

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Highly Cited

2002

Highly Cited

2002

Abstract. We consider the Riemannian geometry defined on a convex set by the Hessian of a self-concordant barrier function, and… Expand

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Highly Cited

2000

Highly Cited

2000

In the first part of this thesis, we introduce a specific class of Linear Matrix Inequalities (LMI) whose optimal solution can be… Expand

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Highly Cited

1989

Highly Cited

1989

This invention relates to a push rod type motion-transmitting mechanism including a main push rod and a pair of auxiliary push… Expand

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