Hits ?▲ |
Authors |
Title |
Venue |
Year |
Link |
Author keywords |
84 | Rafael Molina 0001 |
On the Hierarchical Bayesian Approach to Image Restoration: Applications to Astronomical Images. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Pattern Anal. Mach. Intell. ![In: IEEE Trans. Pattern Anal. Mach. Intell. 16(11), pp. 1122-1128, 1994. The full citation details ...](Pics/full.jpeg) |
1994 |
DBLP DOI BibTeX RDF |
hierarchical Bayesian approach, astronomical images, local characteristics, hyperprior, hyperparameters estimation, noise, image restoration, image restoration, maximum likelihood estimation, Bayes methods, image models, astronomy |
72 | Masayuki Karasuyama, Daisuke Kitakoshi, Ryohei Nakano |
Revised Optimizer of SVR Hyperparameters Minimizing Cross-Validation Error. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IJCNN ![In: Proceedings of the International Joint Conference on Neural Networks, IJCNN 2006, part of the IEEE World Congress on Computational Intelligence, WCCI 2006, Vancouver, BC, Canada, 16-21 July 2006, pp. 319-326, 2006, IEEE, 0-7803-9490-9. The full citation details ...](Pics/full.jpeg) |
2006 |
DBLP DOI BibTeX RDF |
|
59 | G. Haranadh, C. Chandra Sekhar |
Hyperparameters of Gaussian process as features for trajectory classification. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IJCNN ![In: Proceedings of the International Joint Conference on Neural Networks, IJCNN 2008, part of the IEEE World Congress on Computational Intelligence, WCCI 2008, Hong Kong, China, June 1-6, 2008, pp. 2195-2199, 2008, IEEE, 978-1-4244-1820-6. The full citation details ...](Pics/full.jpeg) |
2008 |
DBLP DOI BibTeX RDF |
|
59 | Javier Acevedo, Saturnino Maldonado-Bascón, Philip Siegmann, Sergio Lafuente-Arroyo, Pedro Gil-Jiménez |
Tuning L1-SVM Hyperparameters with Modified Radius Margin Bounds and Simulated Annealing. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IWANN ![In: Computational and Ambient Intelligence, 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebastián, Spain, June 20-22, 2007, Proceedings, pp. 284-291, 2007, Springer, 978-3-540-73006-4. The full citation details ...](Pics/full.jpeg) |
2007 |
DBLP DOI BibTeX RDF |
|
45 | Masayuki Karasuyama, Ryohei Nakano |
Optimizing Sparse Kernel Ridge Regression hyperparameters based on leave-one-out cross-validation. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IJCNN ![In: Proceedings of the International Joint Conference on Neural Networks, IJCNN 2008, part of the IEEE World Congress on Computational Intelligence, WCCI 2008, Hong Kong, China, June 1-6, 2008, pp. 3463-3468, 2008, IEEE, 978-1-4244-1820-6. The full citation details ...](Pics/full.jpeg) |
2008 |
DBLP DOI BibTeX RDF |
|
45 | Masayuki Karasuyama, Ryohei Nakano |
Optimizing SVR Hyperparameters via Fast Cross-Validation using AOSVR. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IJCNN ![In: Proceedings of the International Joint Conference on Neural Networks, IJCNN 2007, Celebrating 20 years of neural networks, Orlando, Florida, USA, August 12-17, 2007, pp. 1186-1191, 2007, IEEE, 978-1-4244-1379-9. The full citation details ...](Pics/full.jpeg) |
2007 |
DBLP DOI BibTeX RDF |
|
43 | Lei Xie 0007 |
Swarm Intelligent Tuning of One-Class nu-SVM Parameters. ![Search on Bibsonomy](Pics/bibsonomy.png) |
RSKT ![In: Rough Sets and Knowledge Technology, First International Conference, RSKT 2006, Chongqing, China, July 24-26, 2006, Proceedings, pp. 552-559, 2006, Springer, 3-540-36297-5. The full citation details ...](Pics/full.jpeg) |
2006 |
DBLP DOI BibTeX RDF |
?-SVM, radical basis function, hyperparameters tuning, particle swarm optimization, Swarm intelligence |
43 | Nuno Vasconcelos, Andrew Lippman |
Empirical Bayesian Motion Segmentation. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Pattern Anal. Mach. Intell. ![In: IEEE Trans. Pattern Anal. Mach. Intell. 23(2), pp. 217-221, 2001. The full citation details ...](Pics/full.jpeg) |
2001 |
DBLP DOI BibTeX RDF |
empirical Bayesian procedures, estimation of hyperparameters, expectation-maximization, Motion segmentation, statistical learning, layered representations |
41 | Liang Zhou, Fuxin Li, Yanwu Yang |
Path Algorithms for One-Class SVM. ![Search on Bibsonomy](Pics/bibsonomy.png) |
ISNN (1) ![In: Advances in Neural Networks - ISNN 2008, 5th International Symposium on Neural Networks, ISNN 2008, Beijing, China, September 24-28, 2008, Proceedings, Part I, pp. 645-654, 2008, Springer, 978-3-540-87731-8. The full citation details ...](Pics/full.jpeg) |
2008 |
DBLP DOI BibTeX RDF |
Path algorithm, Regularization, Kernel, One-Class SVM |
41 | Takashi Isozaki, Noriji Kato, Maomi Ueno |
Minimum Free Energies with "Data Temperature" for Parameter Learning of Bayesian Networks. ![Search on Bibsonomy](Pics/bibsonomy.png) |
ICTAI (1) ![In: 20th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2008), November 3-5, 2008, Dayton, Ohio, USA, Volume 1, pp. 371-378, 2008, IEEE Computer Society, 978-0-7695-3440-4. The full citation details ...](Pics/full.jpeg) |
2008 |
DBLP DOI BibTeX RDF |
|
41 | Tomohiro Hachino, Visakan Kadirkamanathan |
Time Series Forecasting Using Multiple Gaussian Process Prior Model. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CIDM ![In: Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2007, part of the IEEE Symposium Series on Computational Intelligence 2007, Honolulu, Hawaii, USA, 1-5 April 2007, pp. 604-609, 2007, IEEE, 1-4244-0705-2. The full citation details ...](Pics/full.jpeg) |
2007 |
DBLP DOI BibTeX RDF |
|
41 | Hyun-Chul Kim, Zoubin Ghahramani |
Bayesian Gaussian Process Classification with the EM-EP Algorithm. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Pattern Anal. Mach. Intell. ![In: IEEE Trans. Pattern Anal. Mach. Intell. 28(12), pp. 1948-1959, 2006. The full citation details ...](Pics/full.jpeg) |
2006 |
DBLP DOI BibTeX RDF |
Gaussian process classification, expectation propagation, EM-EP algorithm, kernel methods, Bayesian methods |
41 | Rafael Molina 0001, Javier Mateos, Aggelos K. Katsaggelos |
Blind Deconvolution Using a Variational Approach to Parameter, Image, and Blur Estimation. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Image Process. ![In: IEEE Trans. Image Process. 15(12), pp. 3715-3727, 2006. The full citation details ...](Pics/full.jpeg) |
2006 |
DBLP DOI BibTeX RDF |
|
41 | Sambu Seo, Klaus Obermayer |
Dynamic Hyperparameter Scaling Method for LVQ Algorithms. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IJCNN ![In: Proceedings of the International Joint Conference on Neural Networks, IJCNN 2006, part of the IEEE World Congress on Computational Intelligence, WCCI 2006, Vancouver, BC, Canada, 16-21 July 2006, pp. 3196-3203, 2006, IEEE, 0-7803-9490-9. The full citation details ...](Pics/full.jpeg) |
2006 |
DBLP DOI BibTeX RDF |
|
41 | Mathias M. Adankon, Mohamed Cheriet |
New Formulation of SVM for Model Selection. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IJCNN ![In: Proceedings of the International Joint Conference on Neural Networks, IJCNN 2006, part of the IEEE World Congress on Computational Intelligence, WCCI 2006, Vancouver, BC, Canada, 16-21 July 2006, pp. 1900-1907, 2006, IEEE, 0-7803-9490-9. The full citation details ...](Pics/full.jpeg) |
2006 |
DBLP DOI BibTeX RDF |
|
41 | Peter Sollich |
Can Gaussian Process Regression Be Made Robust Against Model Mismatch? ![Search on Bibsonomy](Pics/bibsonomy.png) |
Deterministic and Statistical Methods in Machine Learning ![In: Deterministic and Statistical Methods in Machine Learning, First International Workshop, Sheffield, UK, September 7-10, 2004, Revised Lectures, pp. 199-210, 2004, Springer, 3-540-29073-7. The full citation details ...](Pics/full.jpeg) |
2004 |
DBLP DOI BibTeX RDF |
|
41 | Joaquin Quiñonero Candela, Carl Edward Rasmussen |
Analysis of Some Methods for Reduced Rank Gaussian Process Regression. ![Search on Bibsonomy](Pics/bibsonomy.png) |
European Summer School on Multi-AgentControl ![In: Switching and Learning in Feedback Systems, European Summer School on Multi-Agent Control, Maynooth, Ireland, September 8-10, 2003, Revised Lectures and Selected Papers, pp. 98-127, 2003, Springer, 3-540-24457-3. The full citation details ...](Pics/full.jpeg) |
2003 |
DBLP DOI BibTeX RDF |
|
31 | Alexandre L. M. Levada, Nelson D. A. Mascarenhas, Alberto Tannús |
On the asymptotic variances of Gaussian Markov Random Field model hyperparameters in stochastic image modeling. ![Search on Bibsonomy](Pics/bibsonomy.png) |
ICPR ![In: 19th International Conference on Pattern Recognition (ICPR 2008), December 8-11, 2008, Tampa, Florida, USA, pp. 1-4, 2008, IEEE Computer Society, 978-1-4244-2175-6. The full citation details ...](Pics/full.jpeg) |
2008 |
DBLP DOI BibTeX RDF |
|
31 | Tanasanee Phienthrakul, Boonserm Kijsirikul |
Evolving Hyperparameters of Support Vector Machines Based on Multi-Scale RBF Kernels. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Intelligent Information Processing ![In: Intelligent Information Processing III, IFIP TC12 International Conference on Intelligent Information Processing (IIP 2006), September 20-23, Adelaide, Australia, pp. 269-278, 2006, Springer, 978-0-387-44639-4. The full citation details ...](Pics/full.jpeg) |
2006 |
DBLP DOI BibTeX RDF |
Support Vector Machines, Radial Basis Function, Kernel Methods, Evolutionary Strategies |
29 | John Moses, Malcolm Farrow |
A Procedure for Assessing the Influence of Problem Domain on Effort Estimation Consistency. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Softw. Qual. J. ![In: Softw. Qual. J. 11(4), pp. 283-300, 2003. The full citation details ...](Pics/full.jpeg) |
2003 |
DBLP DOI BibTeX RDF |
Hierarchical Bayesian inference, hyperparameters, interactions with random effects, model fit and checking, deviance statistic, informative and non-informative priors, dependence, effort estimates, COCOMO, linear regression models |
27 | Shihao Ji, David B. Dunson, Lawrence Carin |
Multitask Compressive Sensing. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Signal Process. ![In: IEEE Trans. Signal Process. 57(1), pp. 92-106, 2009. The full citation details ...](Pics/full.jpeg) |
2009 |
DBLP DOI BibTeX RDF |
|
27 | S. Derin Babacan, Rafael Molina 0001, Aggelos K. Katsaggelos |
Variational Bayesian Blind Deconvolution Using a Total Variation Prior. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Image Process. ![In: IEEE Trans. Image Process. 18(1), pp. 12-26, 2009. The full citation details ...](Pics/full.jpeg) |
2009 |
DBLP DOI BibTeX RDF |
|
27 | Roman Garnett, Michael A. Osborne, Stephen J. Roberts |
Sequential Bayesian prediction in the presence of changepoints. ![Search on Bibsonomy](Pics/bibsonomy.png) |
ICML ![In: Proceedings of the 26th Annual International Conference on Machine Learning, ICML 2009, Montreal, Quebec, Canada, June 14-18, 2009, pp. 345-352, 2009, ACM, 978-1-60558-516-1. The full citation details ...](Pics/full.jpeg) |
2009 |
DBLP DOI BibTeX RDF |
|
27 | S. Derin Babacan, Rafael Molina 0001, Aggelos K. Katsaggelos |
Parameter Estimation in TV Image Restoration Using Variational Distribution Approximation. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Image Process. ![In: IEEE Trans. Image Process. 17(3), pp. 326-339, 2008. The full citation details ...](Pics/full.jpeg) |
2008 |
DBLP DOI BibTeX RDF |
|
27 | Gilles Lebrun, Olivier Lezoray, Christophe Charrier, Hubert Cardot |
An EA Multi-model Selection for SVM Multiclass Schemes. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IWANN ![In: Computational and Ambient Intelligence, 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebastián, Spain, June 20-22, 2007, Proceedings, pp. 260-267, 2007, Springer, 978-3-540-73006-4. The full citation details ...](Pics/full.jpeg) |
2007 |
DBLP DOI BibTeX RDF |
|
27 | Masashi Sekino, Katsumi Nitta |
Unbiased Learning for Hierarchical Models. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IJCNN ![In: Proceedings of the International Joint Conference on Neural Networks, IJCNN 2007, Celebrating 20 years of neural networks, Orlando, Florida, USA, August 12-17, 2007, pp. 575-580, 2007, IEEE, 978-1-4244-1379-9. The full citation details ...](Pics/full.jpeg) |
2007 |
DBLP DOI BibTeX RDF |
|
27 | Hugo Jair Escalante, Manuel Montes-y-Gómez, Luis Enrique Sucar |
PSMS for Neural Networks on the IJCNN 2007 Agnostic vs Prior Knowledge Challenge. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IJCNN ![In: Proceedings of the International Joint Conference on Neural Networks, IJCNN 2007, Celebrating 20 years of neural networks, Orlando, Florida, USA, August 12-17, 2007, pp. 678-683, 2007, IEEE, 978-1-4244-1379-9. The full citation details ...](Pics/full.jpeg) |
2007 |
DBLP DOI BibTeX RDF |
|
27 | Yu Fu 0001, Antony Browne |
Using Ensembles of Neural Networks to Improve Automatic Relevance Determination. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IJCNN ![In: Proceedings of the International Joint Conference on Neural Networks, IJCNN 2007, Celebrating 20 years of neural networks, Orlando, Florida, USA, August 12-17, 2007, pp. 1590-1594, 2007, IEEE, 978-1-4244-1379-9. The full citation details ...](Pics/full.jpeg) |
2007 |
DBLP DOI BibTeX RDF |
|
27 | Bruno Feres de Souza, André Carlos Ponce de Leon Ferreira de Carvalho, Rodrigo Calvo, Renato Porfirio Ishii |
Multiclass SVM Model Selection Using Particle Swarm Optimization. ![Search on Bibsonomy](Pics/bibsonomy.png) |
HIS ![In: 6th International Conference on Hybrid Intelligent Systems (HIS 2006), 13-15 December 2006, Auckland, New Zealand, pp. 31, 2006, IEEE Computer Society, 0-7695-2662-4. The full citation details ...](Pics/full.jpeg) |
2006 |
DBLP DOI BibTeX RDF |
|
27 | Desikachari Nadadur, Robert M. Haralick, David E. Gustafson |
A Bayesian framework for noise covariance estimation using the facet model. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Image Process. ![In: IEEE Trans. Image Process. 14(11), pp. 1902-1917, 2005. The full citation details ...](Pics/full.jpeg) |
2005 |
DBLP DOI BibTeX RDF |
|
27 | Amaury Lendasse, Yongnan Ji, Nima Reyhani, Michel Verleysen |
LS-SVM Hyperparameter Selection with a Nonparametric Noise Estimator. ![Search on Bibsonomy](Pics/bibsonomy.png) |
ICANN (2) ![In: Artificial Neural Networks: Formal Models and Their Applications - ICANN 2005, 15th International Conference, Warsaw, Poland, September 11-15, 2005, Proceedings, Part II, pp. 625-630, 2005, Springer, 3-540-28755-8. The full citation details ...](Pics/full.jpeg) |
2005 |
DBLP DOI BibTeX RDF |
Regression, Least Squares Support Vector Machines, Leave-one-out, Noise Estimation |
27 | Zhuo Gao, K. Y. Michael Wong |
Smooth Performance Landscapes of the Variational Bayesian Approach. ![Search on Bibsonomy](Pics/bibsonomy.png) |
ICANN (2) ![In: Artificial Neural Networks: Formal Models and Their Applications - ICANN 2005, 15th International Conference, Warsaw, Poland, September 11-15, 2005, Proceedings, Part II, pp. 241-246, 2005, Springer, 3-540-28755-8. The full citation details ...](Pics/full.jpeg) |
2005 |
DBLP DOI BibTeX RDF |
|
27 | Gilles Cohen, Melanie Hilario, Antoine Geissbühler |
Model Selection for Support Vector Classifiers via Genetic Algorithms. An Application to Medical Decision Support. ![Search on Bibsonomy](Pics/bibsonomy.png) |
ISBMDA ![In: Biological and Medical Data Analysis, 5th International Symposium, ISBMDA 2004, Barcelona, Spain, November 18-19, 2004, Proceedings, pp. 200-211, 2004, Springer, 3-540-23964-2. The full citation details ...](Pics/full.jpeg) |
2004 |
DBLP DOI BibTeX RDF |
|
27 | Jen-Tzung Chien |
Linear regression based Bayesian predictive classification for speech recognition. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Speech Audio Process. ![In: IEEE Trans. Speech Audio Process. 11(1), pp. 70-79, 2003. The full citation details ...](Pics/full.jpeg) |
2003 |
DBLP DOI BibTeX RDF |
|
27 | Nikolaos Nasios, Adrian G. Bors |
Blind Source Separation USing Variational Expectation-Maximization Algorithm. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CAIP ![In: Computer Analysis of Images and Patterns, 10th International Conference, CAIP 2003, Groningen, The Netherlands, August 25-27, 2003, Proceedings, pp. 442-450, 2003, Springer, 3-540-40730-8. The full citation details ...](Pics/full.jpeg) |
2003 |
DBLP DOI BibTeX RDF |
|
27 | Rafael Molina 0001, Aggelos K. Katsaggelos, Javier Mateos |
Bayesian and regularization methods for hyperparameter estimation in image restoration. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Image Process. ![In: IEEE Trans. Image Process. 8(2), pp. 231-246, 1999. The full citation details ...](Pics/full.jpeg) |
1999 |
DBLP DOI BibTeX RDF |
|
18 | Frank Kulwa, Haoshi Zhang, Oluwarotimi Williams Samuel, Mojisola Grace Asogbon, Erik J. Scheme, Rami N. Khushaba, Alistair A. McEwan, Guanglin Li 0001 |
A Multidataset Characterization of Window-Based Hyperparameters for Deep CNN-Driven sEMG Pattern Recognition. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Hum. Mach. Syst. ![In: IEEE Trans. Hum. Mach. Syst. 54(1), pp. 131-142, February 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Mustafa Açikkar |
Fast grid search: A grid search-inspired algorithm for optimizing hyperparameters of support vector regression. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Turkish J. Electr. Eng. Comput. Sci. ![In: Turkish J. Electr. Eng. Comput. Sci. 32(1), pp. 68-92, 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | H. K. Ravikiran, J. Jayanth, M. S. Sathisha, K. Bindu |
Optimizing Sheep Breed Classification with Bat Algorithm-Tuned CNN Hyperparameters. ![Search on Bibsonomy](Pics/bibsonomy.png) |
SN Comput. Sci. ![In: SN Comput. Sci. 5(2), pp. 219, 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Md. Mostafizer Rahman, Yutaka Watanobe |
Multilingual Program Code Classification Using $n$-Layered Bi-LSTM Model With Optimized Hyperparameters. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Emerg. Top. Comput. Intell. ![In: IEEE Trans. Emerg. Top. Comput. Intell. 8(2), pp. 1452-1468, April 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Sandeep Dasari, Rajesh Kaluri |
An Effective Classification of DDoS Attacks in a Distributed Network by Adopting Hierarchical Machine Learning and Hyperparameters Optimization Techniques. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Access ![In: IEEE Access 12, pp. 10834-10845, 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Mohammed Tayebi, Said El Kafhali |
Performance analysis of metaheuristics based hyperparameters optimization for fraud transactions detection. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Evol. Intell. ![In: Evol. Intell. 17(2), pp. 921-939, April 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Mehmet Akif Bülbül |
Optimization of artificial neural network structure and hyperparameters in hybrid model by genetic algorithm: iOS-android application for breast cancer diagnosis/prediction. ![Search on Bibsonomy](Pics/bibsonomy.png) |
J. Supercomput. ![In: J. Supercomput. 80(4), pp. 4533-4553, March 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Zhenyao Liu, Wei-Chang Yeh |
Simplified swarm optimisation for CNN hyperparameters: a sound classification approach. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Int. J. Web Grid Serv. ![In: Int. J. Web Grid Serv. 20(1), pp. 93-113, 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Caroline Choi, Yoonho Lee 0001, Annie S. Chen, Allan Zhou, Aditi Raghunathan, Chelsea Finn |
AutoFT: Robust Fine-Tuning by Optimizing Hyperparameters on OOD Data. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2401.10220, 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Abdelaziz Bensadok, Muhammad Zeeshan Babar |
Fuzzy hyperparameters update in a second order optimization. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2403.15416, 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Sabrina Herbst, Vincenzo De Maio, Ivona Brandic |
On Optimizing Hyperparameters for Quantum Neural Networks. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2403.18579, 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Sungmin Cha, Kyunghyun Cho |
Hyperparameters in Continual Learning: a Reality Check. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2403.09066, 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Nefeli Gkouti, Prodromos Malakasiotis, Stavros Toumpis, Ion Androutsopoulos |
Should I try multiple optimizers when fine-tuning pre-trained Transformers for NLP tasks? Should I tune their hyperparameters? ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2402.06948, 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Juliusz Ziomek, Masaki Adachi, Michael A. Osborne |
Beyond Lengthscales: No-regret Bayesian Optimisation With Unknown Hyperparameters Of Any Type. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2402.01632, 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Bernard Vau, Tudor-Bogdan Airimitoaie |
Recursive identification with regularization and on-line hyperparameters estimation. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2401.00097, 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Wuyang Chen, Junru Wu, Zhangyang Wang, Boris Hanin |
Principled Architecture-aware Scaling of Hyperparameters. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2402.17440, 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Natalija Mitic, Apostolos Pyrgelis, Sinem Sav |
How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2402.16087, 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Hideaki Iiduka |
Theoretical analysis of Adam using hyperparameters close to one without Lipschitz smoothness. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Numer. Algorithms ![In: Numer. Algorithms 95(1), pp. 383-421, January 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Sungyong Baik, Myungsub Choi, Janghoon Choi, Heewon Kim, Kyoung Mu Lee |
Learning to Learn Task-Adaptive Hyperparameters for Few-Shot Learning. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Pattern Anal. Mach. Intell. ![In: IEEE Trans. Pattern Anal. Mach. Intell. 46(3), pp. 1441-1454, March 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Khadija Aguerchi, Younes Jabrane, Maryam Habba, Amir Hajjam El Hassani |
A CNN Hyperparameters Optimization Based on Particle Swarm Optimization for Mammography Breast Cancer Classification. ![Search on Bibsonomy](Pics/bibsonomy.png) |
J. Imaging ![In: J. Imaging 10(2), pp. 30, February 2024. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP DOI BibTeX RDF |
|
18 | Nefeli Gkouti, Prodromos Malakasiotis, Stavros Toumpis, Ion Androutsopoulos |
Should I try multiple optimizers when fine-tuning a pre-trained Transformer for NLP tasks? Should I tune their hyperparameters? ![Search on Bibsonomy](Pics/bibsonomy.png) |
EACL (1) ![In: Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2024 - Volume 1: Long Papers, St. Julian's, Malta, March 17-22, 2024, pp. 2555-2574, 2024, Association for Computational Linguistics, 979-8-89176-088-2. The full citation details ...](Pics/full.jpeg) |
2024 |
DBLP BibTeX RDF |
|
18 | Mingzhou Yin, Roy S. Smith |
Error Bounds for Kernel-Based Linear System Identification With Unknown Hyperparameters. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Control. Syst. Lett. ![In: IEEE Control. Syst. Lett. 7, pp. 2491-2496, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
DBLP DOI BibTeX RDF |
|
18 | Alessandro Sebastianelli, Maria Pia del Rosso, Silvia Liberata Ullo, Paolo Gamba |
On Quantum Hyperparameters Selection in Hybrid Classifiers for Earth Observation Data. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Geosci. Remote. Sens. Lett. ![In: IEEE Geosci. Remote. Sens. Lett. 20, pp. 1-5, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Saghir Ahmed, Basit Raza, Lal Hussain, Amjad Aldweesh, Abdulfattah Omar, Mohammad Shahbaz Khan, Elsayed Tag-Eldin, Muhammad Amin Nadim |
The Deep Learning ResNet101 and Ensemble XGBoost Algorithm with Hyperparameters Optimization Accurately Predict the Lung Cancer. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Appl. Artif. Intell. ![In: Appl. Artif. Intell. 37(1), December 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Jianhui Sun, Ying Yang, Guangxu Xun, Aidong Zhang |
Scheduling Hyperparameters to Improve Generalization: From Centralized SGD to Asynchronous SGD. ![Search on Bibsonomy](Pics/bibsonomy.png) |
ACM Trans. Knowl. Discov. Data ![In: ACM Trans. Knowl. Discov. Data 17(2), pp. 29:1-29:37, February 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Saurabh Shrivastava, Sanyam Shukla, Nilay Khare |
A stable variant of linex loss SVM for handling noise with reduced hyperparameters. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Inf. Sci. ![In: Inf. Sci. 646, pp. 119402, October 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | You-Gan Wang, Jinran Wu, Zhi-Hua Hu, Geoffrey J. McLachlan |
A new algorithm for support vector regression with automatic selection of hyperparameters. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Pattern Recognit. ![In: Pattern Recognit. 133, pp. 108989, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Ying Deng, Xinliang Hu, Da Teng, Bing Li 0001, Congxuan Zhang, Weiming Hu |
Dynamic adjustment of hyperparameters for anchor-based detection of objects with large image size differences. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Pattern Recognit. Lett. ![In: Pattern Recognit. Lett. 167, pp. 196-203, March 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Samia Mezzah, Abdelmalek Tari |
Practical hyperparameters tuning of convolutional neural networks for EEG emotional features classification. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Intell. Syst. Appl. ![In: Intell. Syst. Appl. 18, pp. 200212, May 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Di Wu 0002, Qinghua Guan, Zhe Fan, Hanhui Deng, Tao Wu 0005 |
AutoML With Parallel Genetic Algorithm for Fast Hyperparameters Optimization in Efficient IoT Time Series Prediction. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Ind. Informatics ![In: IEEE Trans. Ind. Informatics 19(9), pp. 9555-9564, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Hafsa Bousbiat, Anthony Faustine, Christoph Klemenjak, Lucas Pereira, Wilfried Elmenreich |
Unlocking the Full Potential of Neural NILM: On Automation, Hyperparameters, and Modular Pipelines. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Ind. Informatics ![In: IEEE Trans. Ind. Informatics 19(5), pp. 7002-7010, May 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Nan Miles Xi, Angelos Vasilopoulos |
Tuning hyperparameters of doublet-detection methods for single-cell RNA sequencing data. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Quant. Biol. ![In: Quant. Biol. 11(3), pp. 297-305, September 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Nicoletta Del Buono, Flavia Esposito, Laura Selicato, Rafal Zdunek |
Bi-level algorithm for optimizing hyperparameters in penalized nonnegative matrix factorization. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Appl. Math. Comput. ![In: Appl. Math. Comput. 457, pp. 128184, November 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Zhiqiang Zeng, Jinping Sun, Yanping Wang, Dandan Gu, Zhu Han 0002, Wen Hong |
Few-Shot SAR Target Recognition Through Meta-Adaptive Hyperparameters' Learning for Fast Adaptation. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Geosci. Remote. Sens. ![In: IEEE Trans. Geosci. Remote. Sens. 61, pp. 1-17, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Debasmita Mishra, Bighnaraj Naik, Janmenjoy Nayak, Alireza Souri, Pandit Byomakesha Dash, S. Vimal 0001 |
Light gradient boosting machine with optimized hyperparameters for identification of malicious access in IoT network. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Digit. Commun. Networks ![In: Digit. Commun. Networks 9(1), pp. 125-137, February 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Dongmei Liu, Haibin Ouyang, Steven Li, Chunliang Zhang, Zhi-Hui Zhan |
Hyperparameters optimization of convolutional neural network based on local autonomous competition harmony search algorithm. ![Search on Bibsonomy](Pics/bibsonomy.png) |
J. Comput. Des. Eng. ![In: J. Comput. Des. Eng. 10(4), pp. 1280-1297, July 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Dingqi Yang, Bingqing Qu, Rana Hussein, Paolo Rosso, Philippe Cudré-Mauroux, Jie Liu 0001 |
Revisiting Embedding Based Graph Analyses: Hyperparameters Matter! ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Knowl. Data Eng. ![In: IEEE Trans. Knowl. Data Eng. 35(11), pp. 11830-11845, November 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Meixuan He, Yuqing Liang, Jinlan Liu, Dongpo Xu |
Convergence of Adam for Non-convex Objectives: Relaxed Hyperparameters and Non-ergodic Case. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2307.11782, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Abel C. H. Chen |
How to Prove the Optimized Values of Hyperparameters for Particle Swarm Optimization? ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2302.00155, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
DBLP DOI BibTeX RDF |
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18 | Césaire J. K. Fouodo, Lea L. Kronziel, Inke R. König, Silke Szymczak |
Effect of hyperparameters on variable selection in random forests. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2309.06943, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Andrea Bonfanti, Roberto Santana 0001, Marco Ellero, Babak Gholami |
On the Hyperparameters influencing a PINN's generalization beyond the training domain. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2302.07557, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Julie Keisler, El-Ghazali Talbi, Sandra Claudel, Gilles Cabriel |
An algorithmic framework for the optimization of deep neural networks architectures and hyperparameters. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2303.12797, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Gustav Bredell, Marcel Fischer, Przemyslaw Szostak, Samaneh Abbasi-Sureshjani, Alvaro Gomariz 0001 |
Aggregation Model Hyperparameters Matter in Digital Pathology. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2311.17804, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Andri Pranolo, Yingchi Mao, Aji Prasetya Wibawa, Agung Bella Putra Utama, Felix Andika Dwiyanto |
Optimized Three Deep Learning Models Based-PSO Hyperparameters for Beijing PM2.5 Prediction. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2306.07296, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Yin-Ting Liao, Hengrui Luo, Anna Ma |
Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2306.00357, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Mingzhou Yin, Roy S. Smith |
Error Bounds for Kernel-Based Linear System Identification with Unknown Hyperparameters. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2303.09842, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Ayoub Arous, Amira Guesmi, Muhammad Abdullah Hanif, Ihsen Alouani, Muhammad Shafique 0001 |
Exploring Machine Learning Privacy/Utility trade-off from a hyperparameters Lens. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2303.01819, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | David Salinas, Jacek Golebiowski, Aaron Klein, Matthias W. Seeger, Cédric Archambeau |
Optimizing Hyperparameters with Conformal Quantile Regression. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2305.03623, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Joris Quist, Yunqiang Li, Jan van Gemert |
Understanding weight-magnitude hyperparameters in training binary networks. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2303.02452, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Paulo J. S. Ferreira, João Mendes-Moreira 0001, João M. P. Cardoso |
A Study on Hyperparameters Configurations for an Efficient Human Activity Recognition System. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2308.13314, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Flavia Esposito, Laura Selicato, Caterina Sportelli |
Theoretical aspects in penalty hyperparameters optimization. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2301.13542, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Tin Lai, Farnaz Farid, Abubakar Bello, Fariza Sabrina |
Ensemble Learning based Anomaly Detection for IoT Cybersecurity via Bayesian Hyperparameters Sensitivity Analysis. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2307.10596, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Manikanta Loya, Divya Anand Sinha, Richard Futrell |
Exploring the Sensitivity of LLMs' Decision-Making Capabilities: Insights from Prompt Variation and Hyperparameters. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2312.17476, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Theresa Eimer, Marius Lindauer, Roberta Raileanu |
Hyperparameters in Reinforcement Learning and How To Tune Them. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2306.01324, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Matthias Bitzer, Mona Meister, Christoph Zimmer |
Amortized Inference for Gaussian Process Hyperparameters of Structured Kernels. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2306.09819, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Jeremy Bernstein, Chris Mingard, Kevin Huang, Navid Azizan, Yisong Yue |
Automatic Gradient Descent: Deep Learning without Hyperparameters. ![Search on Bibsonomy](Pics/bibsonomy.png) |
CoRR ![In: CoRR abs/2304.05187, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Oliver Lloyd, Yi Liu 0058, Tom R. Gaunt |
Assessing the effects of hyperparameters on knowledge graph embedding quality. ![Search on Bibsonomy](Pics/bibsonomy.png) |
J. Big Data ![In: J. Big Data 10(1), pp. 59, December 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Xiyuan Liu, Jia Wu 0005, Senpeng Chen |
Efficient hyperparameters optimization through model-based reinforcement learning with experience exploiting and meta-learning. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Soft Comput. ![In: Soft Comput. 27(13), pp. 8661-8678, July 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Caie Hu, Sanyou Zeng, Changhe Li |
Scalable GP with hyperparameters sharing based on transfer learning for solving expensive optimization problems. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Appl. Soft Comput. ![In: Appl. Soft Comput. 148, pp. 110866, November 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Hanhan Yan, Qiang Li, Ming-Lang Tseng, Xin Guan |
Joint-optimized feature selection and classifier hyperparameters by salp swarm algorithm in piano score difficulty measurement problem. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Appl. Soft Comput. ![In: Appl. Soft Comput. 144, pp. 110464, September 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Alberto Corredera, Carlos Ruiz |
Prescriptive selection of machine learning hyperparameters with applications in power markets: Retailer's optimal trading. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Eur. J. Oper. Res. ![In: Eur. J. Oper. Res. 306(1), pp. 370-388, 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Vishal Asnani, Xi Yin 0001, Tal Hassner, Xiaoming Liu 0002 |
Reverse Engineering of Generative Models: Inferring Model Hyperparameters From Generated Images. ![Search on Bibsonomy](Pics/bibsonomy.png) |
IEEE Trans. Pattern Anal. Mach. Intell. ![In: IEEE Trans. Pattern Anal. Mach. Intell. 45(12), pp. 15477-15493, December 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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18 | Paul Novello, Gaël Poëtte, David Lugato, Pietro Marco Congedo |
Goal-Oriented Sensitivity Analysis of Hyperparameters in Deep Learning. ![Search on Bibsonomy](Pics/bibsonomy.png) |
J. Sci. Comput. ![In: J. Sci. Comput. 94(3), pp. 45, February 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
DBLP DOI BibTeX RDF |
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18 | Yang Liu 0116, Jing Liu, Yifan Li |
Automatic search of architecture and hyperparameters of graph convolutional networks for node classification. ![Search on Bibsonomy](Pics/bibsonomy.png) |
Appl. Intell. ![In: Appl. Intell. 53(9), pp. 11104-11119, May 2023. The full citation details ...](Pics/full.jpeg) |
2023 |
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