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Highly Cited

2003

Highly Cited

2003

Convex programming involves a convex set F ⊆ Rn and a convex cost function c : F → R. The goal of convex programming is to find a…

Highly Cited

2000

Highly Cited

2000

Nonmonotone projected gradient techniques are considered for the minimization of differentiable functions on closed convex sets…

Highly Cited

1996

Highly Cited

1996

The convex hull of a set of points is the smallest convex set that contains the points. This article presents a practical convex…

Highly Cited

1989

Highly Cited

1989

AbstractLet
$$S \subseteq \mathbb{R}^n $$
be a convex set for which there is an oracle with the following property. Given any…

Highly Cited

1980

Highly Cited

1980

Although they play a fundamental role in nearly all branches of mathematics, inequalities are usually obtained by ad hoc methods…

Highly Cited

1977

Highly Cited

1977

A new algorithm, CONVEX, that determines which points of a planar set are vertices of the convex hull of the set is presented. It…

Highly Cited

1965

Highly Cited

1964

Highly Cited

1964

This note gives a construction for minimizing certain twice-differentiable functions on a closed convex subset C, of a Hubert…

Highly Cited

1959

Highly Cited

1959

The method of successive approximation is applied to the problem of obtaining points of minimum distance on two convex sets…

Highly Cited

1952

Highly Cited

1952

so that the set of all convex sets of L is a commutative semigroup under addition. If the situation had been such that it was not…