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Gradient descent

Known as: Descent, Gradient descent optimization, Gradient descent method 
Gradient descent is a first-order iterative optimization algorithm. To find a local minimum of a function using gradient descent, one takes steps… Expand
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2019
Review
2019
Substantial progress has been made recently on developing provably accurate and efficient algorithms for low-rank matrix… Expand
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Review
2019
Review
2019
Network embedding assigns nodes in a network to low-dimensional representations and effectively preserves the network structure… Expand
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Review
2018
Review
2018
In the structure of ANFIS, there are two different parameter groups: premise and consequence. Training ANFIS means determination… Expand
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Review
2018
Review
2018
Low-rank modeling plays a pivotal role in signal processing and machine learning, with applications ranging from collaborative… Expand
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Review
2017
Review
2017
The Web has accumulated a rich source of information, such as text, image, rating, etc, which represent different aspects of user… Expand
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Review
2016
Review
2016
Deep learning has emerged as a highly efficient technique in machine learning to perform text analytics, which includes text… Expand
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Review
2016
Review
2016
Gradient descent optimization algorithms, while increasingly popular, are often used as black-box optimizers, as practical… Expand
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Highly Cited
2016
Highly Cited
2016
The move from hand-designed features to learned features in machine learning has been wildly successful. In spite of this… Expand
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Highly Cited
2005
Highly Cited
2005
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function… Expand
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Highly Cited
1997
Highly Cited
1997
We consider two algorithm for on-line prediction based on a linear model. The algorithms are the well-known Gradient Descent (GD… Expand
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