Optimasi hiperparameter (Indonesian Wikipedia)

Analysis of information sources in references of the Wikipedia article "Optimasi hiperparameter" in Indonesian language version.

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17arxiv.org

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3nips.cc

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3harvard.edu

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2ubc.ca

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2nih.gov

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1springer.com

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1mit.edu

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1chapelle.cc

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1web.archive.org

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arxiv.org

Claesen, Marc; Moor, Bart De (2015). "Hyperparameter Search in Machine Learning". MIC 2015: The XI Metaheuristics International Conference. 14: 1–5. arXiv:1502.02127.
Ziyu, Wang; Frank, Hutter; Masrour, Zoghi; David, Matheson; Nando, de Feitas (2016). "Bayesian Optimization in a Billion Dimensions via Random Embeddings". Journal of Artificial Intelligence Research (dalam bahasa Inggris). 55: 361–387. arXiv:1301.1942. doi:10.1613/jair.4806.
Snoek, Jasper; Larochelle, Hugo; Adams, Ryan (2012). "Practical Bayesian Optimization of Machine Learning Algorithms" (PDF). Advances in Neural Information Processing Systems. arXiv:1206.2944. Bibcode:2012arXiv1206.2944S.
Thornton, Chris; Hutter, Frank; Hoos, Holger; Leyton-Brown, Kevin (2013). "Auto-WEKA: Combined selection and hyperparameter optimization of classification algorithms" (PDF). Knowledge Discovery and Data Mining. arXiv:1208.3719. Bibcode:2012arXiv1208.3719T.
Franceschi, Luca; Donini, Michele; Frasconi, Paolo; Pontil, Massimiliano (2017). "Forward and Reverse Gradient-Based Hyperparameter Optimization" (PDF). Proceedings of the 34th International Conference on Machine Learning. arXiv:1703.01785. Bibcode:2017arXiv170301785F.
Shaban, A., Cheng, C. A., Hatch, N., & Boots, B. (2019, April). Truncated back-propagation for bilevel optimization. In The 22nd International Conference on Artificial Intelligence and Statistics (pp. 1723-1732). PMLR.
Lorraine, J., Vicol, P., & Duvenaud, D. (2018). Optimizing Millions of Hyperparameters by Implicit Differentiation. arXiv preprint arXiv:1911.02590.
Lorraine, J., & Duvenaud, D. (2018). Stochastic hyperparameter optimization through hypernetworks. arXiv preprint arXiv:1802.09419.
MacKay, M., Vicol, P., Lorraine, J., Duvenaud, D., & Grosse, R. (2019). Self-tuning networks: Bilevel optimization of hyperparameters using structured best-response functions. arXiv preprint arXiv:1903.03088.
Bae, J., & Grosse, R. B. (2020). Delta-stn: Efficient bilevel optimization for neural networks using structured response jacobians. Advances in Neural Information Processing Systems, 33, 21725-21737.
Liu, H., Simonyan, K., & Yang, Y. (2018). Darts: Differentiable architecture search. arXiv preprint arXiv:1806.09055.
Li, Ang; Spyra, Ola; Perel, Sagi; Dalibard, Valentin; Jaderberg, Max; Gu, Chenjie; Budden, David; Harley, Tim et al. (2019-02-05). "A Generalized Framework for Population Based Training". arΧiv:1902.01894 [cs.AI].
Jamieson, Kevin; Talwalkar, Ameet (2015-02-27). "Non-stochastic Best Arm Identification and Hyperparameter Optimization". arΧiv:1502.07943 [cs.LG].
Li, Liam; Jamieson, Kevin; Rostamizadeh, Afshin; Gonina, Ekaterina; Hardt, Moritz; Recht, Benjamin; Talwalkar, Ameet (2020-03-16). "A System for Massively Parallel Hyperparameter Tuning". arΧiv:1810.05934v5 [cs.LG].
Li, Lisha; Jamieson, Kevin; DeSalvo, Giulia; Rostamizadeh, Afshin; Talwalkar, Ameet (2020-03-16). "Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization". Journal of Machine Learning Research. 18: 1–52. arXiv:1603.06560.
Diaz, Gonzalo; Fokoue, Achille; Nannicini, Giacomo; Samulowitz, Horst (2017). "An effective algorithm for hyperparameter optimization of neural networks". arΧiv:1705.08520 [cs.AI].
Hazan, Elad; Klivans, Adam; Yuan, Yang (2017). "Hyperparameter Optimization: A Spectral Approach". arΧiv:1706.00764 [cs.LG].

chapelle.cc

Olivier Chapelle; Vladimir Vapnik; Olivier Bousquet; Sayan Mukherjee (2002). "Choosing multiple parameters for support vector machines" (PDF). Machine Learning. 46: 131–159. doi:10.1023/a:1012450327387.

doi.org

Chicco D (December 2017). "Ten quick tips for machine learning in computational biology". BioData Mining. 10 (35): 35. doi:10.1186/s13040-017-0155-3. PMC 5721660. PMID 29234465. Pemeliharaan CS1: DOI bebas tanpa ditandai (link)
Ziyu, Wang; Frank, Hutter; Masrour, Zoghi; David, Matheson; Nando, de Feitas (2016). "Bayesian Optimization in a Billion Dimensions via Random Embeddings". Journal of Artificial Intelligence Research (dalam bahasa Inggris). 55: 361–387. arXiv:1301.1942. doi:10.1613/jair.4806.
Hutter, Frank; Hoos, Holger; Leyton-Brown, Kevin (2011), "Sequential Model-Based Optimization for General Algorithm Configuration", Learning and Intelligent Optimization (PDF), Lecture Notes in Computer Science, vol. 6683, hlm. 507–523, doi:10.1007/978-3-642-25566-3_40, ISBN 978-3-642-25565-6
Larsen, Jan; Hansen, Lars Kai; Svarer, Claus; Ohlsson, M (1996). "Design and regularization of neural networks: The optimal use of a validation set" (PDF). Neural Networks for Signal Processing VI. Proceedings of the 1996 IEEE Signal Processing Society Workshop. hlm. 62–71. CiteSeerX 10.1.1.415.3266. doi:10.1109/NNSP.1996.548336. ISBN 0-7803-3550-3.
Olivier Chapelle; Vladimir Vapnik; Olivier Bousquet; Sayan Mukherjee (2002). "Choosing multiple parameters for support vector machines" (PDF). Machine Learning. 46: 131–159. doi:10.1023/a:1012450327387.
Kousiouris G, Cuccinotta T, Varvarigou T (2011). "The effects of scheduling, workload type and consolidation scenarios on virtual machine performance and their prediction through optimized artificial neural networks". Journal of Systems and Software. 84 (8): 1270–1291. doi:10.1016/j.jss.2011.04.013.
López-Ibáñez, Manuel; Dubois-Lacoste, Jérémie; Pérez Cáceres, Leslie; Stützle, Thomas; Birattari, Mauro (2016). "The irace package: Iterated Racing for Automatic Algorithm Configuration". Operations Research Perspective. 3 (3): 43–58. doi:10.1016/j.orp.2016.09.002.

dtu.dk

orbit.dtu.dk

Larsen, Jan; Hansen, Lars Kai; Svarer, Claus; Ohlsson, M (1996). "Design and regularization of neural networks: The optimal use of a validation set" (PDF). Neural Networks for Signal Processing VI. Proceedings of the 1996 IEEE Signal Processing Society Workshop. hlm. 62–71. CiteSeerX 10.1.1.415.3266. doi:10.1109/NNSP.1996.548336. ISBN 0-7803-3550-3.

harvard.edu

ui.adsabs.harvard.edu

Snoek, Jasper; Larochelle, Hugo; Adams, Ryan (2012). "Practical Bayesian Optimization of Machine Learning Algorithms" (PDF). Advances in Neural Information Processing Systems. arXiv:1206.2944. Bibcode:2012arXiv1206.2944S.
Thornton, Chris; Hutter, Frank; Hoos, Holger; Leyton-Brown, Kevin (2013). "Auto-WEKA: Combined selection and hyperparameter optimization of classification algorithms" (PDF). Knowledge Discovery and Data Mining. arXiv:1208.3719. Bibcode:2012arXiv1208.3719T.
Franceschi, Luca; Donini, Michele; Frasconi, Paolo; Pontil, Massimiliano (2017). "Forward and Reverse Gradient-Based Hyperparameter Optimization" (PDF). Proceedings of the 34th International Conference on Machine Learning. arXiv:1703.01785. Bibcode:2017arXiv170301785F.

jmlr.org

Domke, Justin (2012). "Generic Methods for Optimization-Based Modeling" (PDF). Aistats. 22. Diarsipkan dari asli (PDF) tanggal 2014-01-24. Diakses tanggal 2017-12-09.

mit.edu

jmlr.csail.mit.edu

Bergstra, James; Bengio, Yoshua (2012). "Random Search for Hyper-Parameter Optimization" (PDF). Journal of Machine Learning Research. 13: 281–305.

mlr.press

proceedings.mlr.press

Franceschi, Luca; Donini, Michele; Frasconi, Paolo; Pontil, Massimiliano (2017). "Forward and Reverse Gradient-Based Hyperparameter Optimization" (PDF). Proceedings of the 34th International Conference on Machine Learning. arXiv:1703.01785. Bibcode:2017arXiv170301785F.

nih.gov

ncbi.nlm.nih.gov

Chicco D (December 2017). "Ten quick tips for machine learning in computational biology". BioData Mining. 10 (35): 35. doi:10.1186/s13040-017-0155-3. PMC 5721660. PMID 29234465. Pemeliharaan CS1: DOI bebas tanpa ditandai (link)

pubmed.ncbi.nlm.nih.gov

Chicco D (December 2017). "Ten quick tips for machine learning in computational biology". BioData Mining. 10 (35): 35. doi:10.1186/s13040-017-0155-3. PMC 5721660. PMID 29234465. Pemeliharaan CS1: DOI bebas tanpa ditandai (link)

nips.cc

papers.nips.cc

Bergstra, James; Bardenet, Remi; Bengio, Yoshua; Kegl, Balazs (2011), "Algorithms for hyper-parameter optimization" (PDF), Advances in Neural Information Processing SystemsBergstra, James; Bardenet, Remi; Bengio, Yoshua; Kegl, Balazs (2011), "Algorithms for hyper-parameter optimization" (PDF), Advances in Neural Information Processing Systems
Snoek, Jasper; Larochelle, Hugo; Adams, Ryan (2012). "Practical Bayesian Optimization of Machine Learning Algorithms" (PDF). Advances in Neural Information Processing Systems. arXiv:1206.2944. Bibcode:2012arXiv1206.2944S.
Chuong B; Chuan-Sheng Foo; Andrew Y Ng (2008). "Efficient multiple hyperparameter learning for log-linear models" (PDF). Advances in Neural Information Processing Systems. 20.

ntu.edu.tw

csie.ntu.edu.tw

Chin-Wei Hsu, Chih-Chung Chang and Chih-Jen Lin (2010). A practical guide to support vector classification. Technical Report, National Taiwan University.

psu.edu

citeseerx.ist.psu.edu

Larsen, Jan; Hansen, Lars Kai; Svarer, Claus; Ohlsson, M (1996). "Design and regularization of neural networks: The optimal use of a validation set" (PDF). Neural Networks for Signal Processing VI. Proceedings of the 1996 IEEE Signal Processing Society Workshop. hlm. 62–71. CiteSeerX 10.1.1.415.3266. doi:10.1109/NNSP.1996.548336. ISBN 0-7803-3550-3.

sciencedirect.com

Kousiouris G, Cuccinotta T, Varvarigou T (2011). "The effects of scheduling, workload type and consolidation scenarios on virtual machine performance and their prediction through optimized artificial neural networks". Journal of Systems and Software. 84 (8): 1270–1291. doi:10.1016/j.jss.2011.04.013.

springer.com

link.springer.com

Matthias Feurer and Frank Hutter. Hyperparameter optimization. In: AutoML: Methods, Systems, Challenges, pages 3–38.

ubc.ca

cs.ubc.ca

Hutter, Frank; Hoos, Holger; Leyton-Brown, Kevin (2011), "Sequential Model-Based Optimization for General Algorithm Configuration", Learning and Intelligent Optimization (PDF), Lecture Notes in Computer Science, vol. 6683, hlm. 507–523, doi:10.1007/978-3-642-25566-3_40, ISBN 978-3-642-25565-6
Thornton, Chris; Hutter, Frank; Hoos, Holger; Leyton-Brown, Kevin (2013). "Auto-WEKA: Combined selection and hyperparameter optimization of classification algorithms" (PDF). Knowledge Discovery and Data Mining. arXiv:1208.3719. Bibcode:2012arXiv1208.3719T.

web.archive.org

Domke, Justin (2012). "Generic Methods for Optimization-Based Modeling" (PDF). Aistats. 22. Diarsipkan dari asli (PDF) tanggal 2014-01-24. Diakses tanggal 2017-12-09.