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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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