In mathematical optimization, statistics, decision theory and machine learning, a loss function or cost function is a function that maps an event orâ€¦Â (More)

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

Review

2016

Review

2016

Rapid progress in machine learning and artificial intelligence (AI) has brought increasing attention to the potential impacts ofâ€¦Â (More)

Is this relevant?

Highly Cited

2016

Highly Cited

2016

- Justin Johnson, Alexandre Alahi, Li Fei-Fei
- ECCV
- 2016

We consider image transformation problems, where an input image is transformed into an output image. Recent methods for suchâ€¦Â (More)

Is this relevant?

Highly Cited

2016

Highly Cited

2016

- De Cheng, Yihong Gong, Sanping Zhou, Jinjun Wang, Nanning Zheng
- 2016 IEEE Conference on Computer Vision andâ€¦
- 2016

Person re-identification across cameras remains a very challenging problem, especially when there are no overlapping fields ofâ€¦Â (More)

Is this relevant?

Highly Cited

2005

Highly Cited

2005

It has long been customary to measure the adequacy of an estimator by the smallness of its mean squared error. The least squaresâ€¦Â (More)

Is this relevant?

Highly Cited

2004

Highly Cited

2004

- Lorenzo Rosasco, Ernesto De Vito, Andrea Caponnetto, Michele Piana, Alessandro Verri
- Neural Computation
- 2004

In this letter, we investigate the impact of choosing different loss functions from the viewpoint of statistical learning theoryâ€¦Â (More)

Is this relevant?

Highly Cited

2000

Highly Cited

2000

- Frank Schorfheide, Yongsung Chang
- 2000

In this paper we propose a Bayesian econometric procedure for the evaluation and comparison of DSGE models. Unlike in manyâ€¦Â (More)

Is this relevant?

Highly Cited

1999

Highly Cited

1999

Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.orgâ€¦Â (More)

Is this relevant?

Highly Cited

1998

Highly Cited

1998

- David Haussler, Jyrki Kivinen, Manfred K. Warmuth
- IEEE Trans. Information Theory
- 1998

We consider adaptive sequential prediction of arbitrary binary sequences when the performance is evaluated using a general lossâ€¦Â (More)

Is this relevant?

Highly Cited

1996

Highly Cited

1996

- Ron Kohavi, David Wolpert
- ICML
- 1996

We present a bias variance decomposition of expected misclassi cation rate the most commonly used loss function in supervisedâ€¦Â (More)

Is this relevant?

Highly Cited

1981