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Gradient

Known as: Grad, Gradient Operator, Gradient of a scalar 
In mathematics, the gradient is a generalization of the usual concept of derivative to functions of several variables. If f(x1, ..., xn) is a… 
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Papers overview

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Highly Cited
2014
Highly Cited
2014
In this paper we consider deterministic policy gradient algorithms for reinforcement learning with continuous actions. The… 
Highly Cited
2011
Highly Cited
2011
In this paper we propose a new framework for learning from large scale datasets based on iterative learning from small mini… 
Highly Cited
2006
Highly Cited
2006
We present a new nonempirical density functional generalized gradient approximation (GGA) that gives significant improvements for… 
Review
2005
Review
2005
  • N. Dalal, B. Triggs
  • IEEE Computer Society Conference on Computer…
  • 2005
  • Corpus ID: 206590483
We study the question of feature sets for robust visual object recognition; adopting linear SVM based human detection as a test… 
Highly Cited
2004
Highly Cited
2004
This article presents a general class of associative reinforcement learning algorithms for connectionist networks containing… 
Highly Cited
2002
Highly Cited
2002
We present a new method for rendering high dynamic range images on conventional displays. Our method is conceptually simple… 
Highly Cited
1999
Highly Cited
1999
Function approximation is essential to reinforcement learning, but the standard approach of approximating a value function and… 
Review
1998
Review
1998
Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based… 
Highly Cited
1998
Highly Cited
1998
  • S. Amari
  • Neural Computation
  • 1998
  • Corpus ID: 207585383
When a parameter space has a certain underlying structure, the ordinary gradient of a function does not represent its steepest… 
Highly Cited
1992
Highly Cited
1992
The problem of finding a root of the multivariate gradient equation that arises in function minimization is considered. When only…