Descent direction

In optimization, a descent direction is a vector that, in the sense below, moves us closer towards a local minimum of our objective function… (More)
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Topic mentions per year

Topic mentions per year

1980-2017
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Papers overview

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2015
2015
We prove the equivalence of two online learning algorithms: 1) mirror descent and 2) natural gradient descent. Both mirror… (More)
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2014
2014
We present a fast distributed solution to the convex network flow optimization problem. Our approach uses a family of dual… (More)
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2014
2014
Metric Temporal Logic (MTL) specifications can capture complex state and timing requirements. Given a nonlinear dynamical system… (More)
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2013
2013
The automatic analysis of transient properties of nonlinear dynamical systems is a challenging problem. The problem is even more… (More)
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Highly Cited
2013
Highly Cited
2013
In this paper we analyze several new methods for solving optimization problems with the objective function formed as a sum of two… (More)
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2012
2012
Given data points p0, . . . , pN on a closed submanifold M of R n and time instants 0 = t0 < t1 < . . . < tN = 1, we consider the… (More)
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2011
2011
Conjugate gradient methods are widely used for solving large-scale unconstrained optimization problems, because they do not need… (More)
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2010
2010
In this paper, we suggest to use a steepest descent algorithm for learning a parametric dictionary in which the structure or atom… (More)
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2009
2009
In this paper, a rank-one updated method for solving symmetric nonlinear equations is proposed. This method possesses some… (More)
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Highly Cited
2005
Highly Cited
2005
In this paper, we propose a modified Polak–Ribière–Polyak (PRP) conjugate gradient method. An attractive property of the proposed… (More)
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