Loosely speaking, a residual is the error in a result. To be precise, suppose we want to find x such that Given an approximation x0 of x, theâ€¦Â (More)

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Highly Cited

2017

Highly Cited

2017

Very deep convolutional networks have been central to the largest advances in image recognition performance in recent years. Oneâ€¦Â (More)

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Highly Cited

2017

Highly Cited

2017

- Saining Xie, Ross B. Girshick, Piotr DollÃ¡r, Zhuowen Tu, Kaiming He
- 2017 IEEE Conference on Computer Vision andâ€¦
- 2017

We present a simple, highly modularized network architecture for image classification. Our network is constructed by repeating aâ€¦Â (More)

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Highly Cited

2016

Highly Cited

2016

- Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
- 2016 IEEE Conference on Computer Vision andâ€¦
- 2016

Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networksâ€¦Â (More)

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Highly Cited

2016

Highly Cited

2016

- Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
- ECCV
- 2016

Deep residual networks [1] have emerged as a family of extremely deep architectures showing compelling accuracy and niceâ€¦Â (More)

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Highly Cited

2016

Highly Cited

2016

- Sergey Zagoruyko, Nikos Komodakis
- BMVC
- 2016

Deep residual networks were shown to be able to scale up to thousands of layers and still have improving performance. Howeverâ€¦Â (More)

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Highly Cited

2007

Highly Cited

2007

- Xiaodi Hou, Liqing Zhang
- 2007 IEEE Conference on Computer Vision andâ€¦
- 2007

The ability of human visual system to detect visual saliency is extraordinarily fast and reliable. However, computationalâ€¦Â (More)

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Highly Cited

2002

Highly Cited

2002

A computer system is described in which isolated words, spoken by a designated talker, are recognized through calculation of aâ€¦Â (More)

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Highly Cited

1995

Highly Cited

1995

- Leemon C. Baird
- ICML
- 1995

A number of reinforcement learning algorithms have been developed that are guaranteed to converge to the optimal solution whenâ€¦Â (More)

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Highly Cited

1994

Highly Cited

1994

- Robert Tibshirani, ROBERT TIBSHIRANIt
- 1994

We propose a new method for estimation in linear models. The \lasso" minimizes the residual sum of squares subject to the sum ofâ€¦Â (More)

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Highly Cited

1991

Highly Cited

1991

- Roland W. Freund, Mark W Nachtigal, Noel M. Nachtigal, Noel M. Nachtigai
- 1991

The biconjugate gradient (BCG) method is the \natural" generalization of the classical conjugate gradient algorithm for Hermitianâ€¦Â (More)

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