超参数 (机器学习) (Chinese Wikipedia)

Analysis of information sources in references of the Wikipedia article "超参数 (机器学习)" in Chinese language version.

refsWebsite

Global rank Chinese rank

8arxiv.org

69^th place

254^th place

6harvard.edu

18^th place

57^th place

2semanticscholar.org

11^th place

332^nd place

2doi.org

2^nd place

23^rd place

2web.archive.org

1^st place

1sciencedirect.com

149^th place

292^nd place

1worldcat.org

5^th place

12^th place

1mlr.press

low place

1nih.gov

4^th place

5^th place

1in2p3.fr

low place

arxiv.org (Global: 69^th place; Chinese: 254^th place)

Yang, Li; Shami, Abdallah. On hyperparameter optimization of machine learning algorithms: Theory and practice. Neurocomputing. 2020-11-20, 415: 295–316. ISSN 0925-2312. S2CID 220919678. arXiv:2007.15745 . doi:10.1016/j.neucom.2020.07.061 （英语）.
Claesen, Marc, and Bart De Moor. "Hyperparameter Search in Machine Learning." arXiv preprint arXiv:1502.02127 (2015).. Bibcode:2015arXiv150202127C. arXiv:1502.02127 .
Probst, Philipp, Bernd Bischl, and Anne-Laure Boulesteix. "Tunability: Importance of Hyperparameters of Machine Learning Algorithms." arXiv preprint arXiv:1802.09596 (2018).. Bibcode:2018arXiv180209596P. arXiv:1802.09596 .
Greff, K.; Srivastava, R. K.; Koutník, J.; Steunebrink, B. R.; Schmidhuber, J. LSTM: A Search Space Odyssey. IEEE Transactions on Neural Networks and Learning Systems. October 23, 2017, 28 (10): 2222–2232. PMID 27411231. S2CID 3356463. arXiv:1503.04069 . doi:10.1109/TNNLS.2016.2582924.
Breuel, Thomas M. "Benchmarking of LSTM networks." arXiv preprint arXiv:1508.02774 (2015).. Bibcode:2015arXiv150802774B. arXiv:1508.02774 .
Revisiting Small Batch Training for Deep Neural Networks (2018).. Bibcode:2018arXiv180407612M. arXiv:1804.07612 .
Claesen, Marc, and Bart De Moor. "Hyperparameter Search in Machine Learning." arXiv preprint arXiv:1502.02127 (2015).. Bibcode:2015arXiv150202127C. arXiv:1502.02127 .
Mania, Horia, Aurelia Guy, and Benjamin Recht. "Simple random search provides a competitive approach to reinforcement learning." arXiv preprint arXiv:1803.07055 (2018).. Bibcode:2018arXiv180307055M. arXiv:1803.07055 .

doi.org (Global: 2^nd place; Chinese: 23^rd place)

Yang, Li; Shami, Abdallah. On hyperparameter optimization of machine learning algorithms: Theory and practice. Neurocomputing. 2020-11-20, 415: 295–316. ISSN 0925-2312. S2CID 220919678. arXiv:2007.15745 . doi:10.1016/j.neucom.2020.07.061 （英语）.
Greff, K.; Srivastava, R. K.; Koutník, J.; Steunebrink, B. R.; Schmidhuber, J. LSTM: A Search Space Odyssey. IEEE Transactions on Neural Networks and Learning Systems. October 23, 2017, 28 (10): 2222–2232. PMID 27411231. S2CID 3356463. arXiv:1503.04069 . doi:10.1109/TNNLS.2016.2582924.

harvard.edu (Global: 18^th place; Chinese: 57^th place)

ui.adsabs.harvard.edu

Claesen, Marc, and Bart De Moor. "Hyperparameter Search in Machine Learning." arXiv preprint arXiv:1502.02127 (2015).. Bibcode:2015arXiv150202127C. arXiv:1502.02127 .
Probst, Philipp, Bernd Bischl, and Anne-Laure Boulesteix. "Tunability: Importance of Hyperparameters of Machine Learning Algorithms." arXiv preprint arXiv:1802.09596 (2018).. Bibcode:2018arXiv180209596P. arXiv:1802.09596 .
Breuel, Thomas M. "Benchmarking of LSTM networks." arXiv preprint arXiv:1508.02774 (2015).. Bibcode:2015arXiv150802774B. arXiv:1508.02774 .
Revisiting Small Batch Training for Deep Neural Networks (2018).. Bibcode:2018arXiv180407612M. arXiv:1804.07612 .
Claesen, Marc, and Bart De Moor. "Hyperparameter Search in Machine Learning." arXiv preprint arXiv:1502.02127 (2015).. Bibcode:2015arXiv150202127C. arXiv:1502.02127 .
Mania, Horia, Aurelia Guy, and Benjamin Recht. "Simple random search provides a competitive approach to reinforcement learning." arXiv preprint arXiv:1803.07055 (2018).. Bibcode:2018arXiv180307055M. arXiv:1803.07055 .

in2p3.fr (Global: low place; Chinese: low place)

indico.lal.in2p3.fr

Greff, Klaus, and Jürgen Schmidhuber. "Introducing Sacred: A Tool to Facilitate Reproducible Research." (PDF). 2015 [2022-11-09]. （原始内容存档 (PDF)于2018-04-07）.

mlr.press (Global: low place; Chinese: low place)

proceedings.mlr.press

Leyton-Brown, Kevin; Hoos, Holger; Hutter, Frank. An Efficient Approach for Assessing Hyperparameter Importance: 754–762. January 27, 2014 [2022-11-09]. （原始内容存档于2022-05-20） –通过proceedings.mlr.press.

nih.gov (Global: 4^th place; Chinese: 5^th place)

ncbi.nlm.nih.gov

Greff, K.; Srivastava, R. K.; Koutník, J.; Steunebrink, B. R.; Schmidhuber, J. LSTM: A Search Space Odyssey. IEEE Transactions on Neural Networks and Learning Systems. October 23, 2017, 28 (10): 2222–2232. PMID 27411231. S2CID 3356463. arXiv:1503.04069 . doi:10.1109/TNNLS.2016.2582924.

sciencedirect.com (Global: 149^th place; Chinese: 292^nd place)

Yang, Li; Shami, Abdallah. On hyperparameter optimization of machine learning algorithms: Theory and practice. Neurocomputing. 2020-11-20, 415: 295–316. ISSN 0925-2312. S2CID 220919678. arXiv:2007.15745 . doi:10.1016/j.neucom.2020.07.061 （英语）.

semanticscholar.org (Global: 11^th place; Chinese: 332^nd place)

api.semanticscholar.org

Yang, Li; Shami, Abdallah. On hyperparameter optimization of machine learning algorithms: Theory and practice. Neurocomputing. 2020-11-20, 415: 295–316. ISSN 0925-2312. S2CID 220919678. arXiv:2007.15745 . doi:10.1016/j.neucom.2020.07.061 （英语）.
Greff, K.; Srivastava, R. K.; Koutník, J.; Steunebrink, B. R.; Schmidhuber, J. LSTM: A Search Space Odyssey. IEEE Transactions on Neural Networks and Learning Systems. October 23, 2017, 28 (10): 2222–2232. PMID 27411231. S2CID 3356463. arXiv:1503.04069 . doi:10.1109/TNNLS.2016.2582924.

web.archive.org (Global: 1^st place; Chinese: 1^st place)

Leyton-Brown, Kevin; Hoos, Holger; Hutter, Frank. An Efficient Approach for Assessing Hyperparameter Importance: 754–762. January 27, 2014 [2022-11-09]. （原始内容存档于2022-05-20） –通过proceedings.mlr.press.
Greff, Klaus, and Jürgen Schmidhuber. "Introducing Sacred: A Tool to Facilitate Reproducible Research." (PDF). 2015 [2022-11-09]. （原始内容存档 (PDF)于2018-04-07）.

worldcat.org (Global: 5^th place; Chinese: 12^th place)

Yang, Li; Shami, Abdallah. On hyperparameter optimization of machine learning algorithms: Theory and practice. Neurocomputing. 2020-11-20, 415: 295–316. ISSN 0925-2312. S2CID 220919678. arXiv:2007.15745 . doi:10.1016/j.neucom.2020.07.061 （英语）.

超参数 (机器学习) (Chinese Wikipedia)

arxiv.org (Global: 69th place; Chinese: 254th place)

doi.org (Global: 2nd place; Chinese: 23rd place)

harvard.edu (Global: 18th place; Chinese: 57th place)