General • 57 methods
Regularization strategies are designed to reduce the test error of a machine learning algorithm, possibly at the expense of training error. Many different forms of regularization exist in the field of deep learning. Below you can find a constantly updating list of regularization strategies.
Subcategories
Method | Year | Papers |
---|---|---|
2014 | 18820 | |
1985 | 9202 | |
2018 | 7457 | |
1943 | 7451 | |
2016 | 767 | |
2018 | 456 | |
1995 | 366 | |
2016 | 314 | |
2019 | 168 | |
2015 | 133 | |
2018 | 130 | |
2018 | 120 | |
2018 | 89 | |
2013 | 77 | |
1986 | 66 | |
2015 | 58 | |
2020 | 57 | |
2000 | 54 | |
2017 | 49 | |
2017 | 49 | |
2014 | 27 | |
2016 | 27 | |
2018 | 26 | |
2016 | 22 | |
2018 | 22 | |
2016 | 20 | |
2022 | 16 | |
2016 | 15 | |
2017 | 14 | |
2020 | 13 | |
2019 | 12 | |
2021 | 10 | |
2019 | 10 | |
2019 | 9 | |
2013 | 7 | |
2017 | 5 | |
2018 | 4 | |
2022 | 4 | |
2018 | 3 | |
2020 | 3 | |
2016 | 3 | |
2021 | 3 | |
2020 | 3 | |
2019 | 3 | |
2016 | 2 | |
2019 | 2 | |
2017 | 2 | |
2023 | 2 | |
2017 | 2 | |
2020 | 1 | |
2021 | 1 | |
2017 | 1 | |
2023 | 1 | |
2021 | 1 | |
2015 | 0 |