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Semantic Scholar uses AI to extract papers important to this topic.

2017

2017

Classical stochastic gradient methods for optimization rely on noisy gradient approximations that become progressively less… Expand

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2015

2015

An adaptive voltage-sensor-based maximum power point tracking algorithm employing a variable scaling factor for a single-ended… Expand

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2004

2004

A new class of methods for the solution of stiff initial value problems is introduced that is parallel by design. It has a two… Expand

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Highly Cited

2000

Highly Cited

2000

We have shown previously that non-stationary signals recorded in a static multi-path environment can often be recovered by… Expand

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Highly Cited

1999

Highly Cited

1999

In this paper the development, convergence theory and numerical testing of a class of gradient unconstrained minimization… Expand

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Highly Cited

1998

Highly Cited

1998

We consider an incremental gradient method with momentum term for minimizing the sum of continuously differentiable functions… Expand

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1996

1996

Computation of shortest paths on free-form surfaces is an important problem in ship design, robot motion planning, computation of… Expand

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Highly Cited

1993

Highly Cited

1993

The step size of this adaptive filter is changed according to a gradient descent algorithm designed to reduce the squared… Expand

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Highly Cited

1991

Highly Cited

1991

Abstract This paper describes a speaker-independent phoneme and word recognition system based on a recurrent error propagation… Expand

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Highly Cited

1968

Highly Cited

1968

Fixed step size random search for minimization of functions of several parameters is described and compared with the fixed step… Expand

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