Sandro Ridella
Orcid: 0000-0003-0612-8219
According to our database1,
Sandro Ridella
authored at least 100 papers
between 1986 and 2023.
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Bibliography
2023
Neurocomputing, July, 2023
2022
Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022
2021
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021
2020
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020
2019
2018
Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels.
IEEE Trans. Neural Networks Learn. Syst., 2018
Randomized learning: Generalization performance of old and new theoretically grounded algorithms.
Neurocomputing, 2018
2017
Pattern Recognit. Lett., 2017
Generalization Performances of Randomized Classifiers and Algorithms built on Data Dependent Distributions.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017
2016
ACM Trans. Embed. Comput. Syst., 2016
PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis.
Pattern Recognit. Lett., 2016
Neural Process. Lett., 2016
Mach. Learn., 2016
Tuning the Distribution Dependent Prior in the PAC-Bayes Framework based on Empirical Data.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016
2015
Neural Networks, 2015
Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency.
Neurocomputing, 2015
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
Support vector machines and strictly positive definite kernel: The regularization hyperparameter is more important than the kernel hyperparameters.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
2014
A Deep Connection Between the Vapnik-Chervonenkis Entropy and the Rademacher Complexity.
IEEE Trans. Neural Networks Learn. Syst., 2014
Unlabeled patterns to tighten Rademacher complexity error bounds for kernel classifiers.
Pattern Recognit. Lett., 2014
Smartphone battery saving by bit-based hypothesis spaces and local Rademacher Complexities.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014
Proceedings of the 2014 IEEE International Conference on Data Mining Workshops, 2014
Learning with few bits on small-scale devices: From regularization to energy efficiency.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014
2013
An improved analysis of the Rademacher data-dependent bound using its self bounding property.
Neural Networks, 2013
J. Artif. Intell. Soft Comput. Res., 2013
A support vector machine classifier from a bit-constrained, sparse and localized hypothesis space.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2013, 2013
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013
2012
In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines.
IEEE Trans. Neural Networks Learn. Syst., 2012
Neural Process. Lett., 2012
Rademacher Complexity and Structural Risk Minimization: An Application to Human Gene Expression Datasets.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012
2011
J. Circuits Syst. Comput., 2011
The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011
Selecting the hypothesis space for improving the generalization ability of Support Vector Machines.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011
Proceedings of the IEEE Symposium on Foundations of Computational Intelligence, 2011
Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011
2010
Using unsupervised analysis to constrain generalization bounds for support vector classifiers.
IEEE Trans. Neural Networks, 2010
Proceedings of the International Joint Conference on Neural Networks, 2010
Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory.
Proceedings of the International Joint Conference on Neural Networks, 2010
2009
K-Fold Cross Validation for Error Rate Estimate in Support Vector Machines.
Proceedings of The 2009 International Conference on Data Mining, 2009
2008
Using Variable Neighborhood Search to improve the Support Vector Machine performance in embedded automotive applications.
Proceedings of the International Joint Conference on Neural Networks, 2008
2007
Proceedings of the International Joint Conference on Neural Networks, 2007
2006
IEEE Trans. Neural Networks, 2006
Appl. Math. Comput., 2006
Proceedings of the International Joint Conference on Neural Networks, 2006
2004
Proceedings of the Biological and Artificial Intelligence Environments, 2004
2003
IEEE Trans. Neural Networks, 2003
A digital architecture for support vector machines: theory, algorithm, and FPGA implementation.
IEEE Trans. Neural Networks, 2003
2002
Proceedings of the Artificial Neural Networks, 2002
2001
Empirical measure of multiclass generalization performance: the K-winner machine case.
IEEE Trans. Neural Networks, 2001
2000
Evaluating the Generalization Ability of Support Vector Machines through the Bootstrap.
Neural Process. Lett., 2000
Int. J. Neural Syst., 2000
Augmenting vector quantization with interval arithmetics for image-coding applications.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2000
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000
1999
IEEE Trans. Neural Networks, 1999
IEEE Trans. Neural Networks, 1999
IEEE Trans. Neural Networks, 1999
Possibility and Necessity Pattern Classification using an Interval Arithmetic Perceptron.
Neural Comput. Appl., 1999
Proceedings of the International Joint Conference Neural Networks, 1999
Support Vector Machines: A Comparison of Some Kernel Functions.
Proceedings of the Third ICSC Symposia on Intelligent Industrial Automation (IIA'99) and Soft Computing (SOCO'99), 1999
1998
1997
IEEE Trans. Neural Networks, 1997
Proceedings of International Conference on Neural Networks (ICNN'97), 1997
Proceedings of International Conference on Neural Networks (ICNN'97), 1997
1996
Limiting the effects of weight errors in feedforward networks using interval arithmetic.
Proceedings of International Conference on Neural Networks (ICNN'96), 1996
1995
Neural Comput. Appl., 1995
Proceedings of the 3rd European Symposium on Artificial Neural Networks, 1995
1994
Neural Comput. Appl., 1994
Neural Comput. Appl., 1994
1993
Neural Networks, 1993
Proceedings of International Conference on Neural Networks (ICNN'88), San Francisco, CA, USA, March 28, 1993
1992
IEEE Trans. Neural Networks, 1992
Parallel Comput., 1992
Complex Syst., 1992
1991
Efficient computation of the correlation dimension from a time series on a LIW computer.
Parallel Comput., 1991
1989
Corrigenda: "Minimizing Multimodal Functions of Continuous Variables with the 'Simulated Annealing' Algorithm".
ACM Trans. Math. Softw., 1989
1988
Parallel Comput., 1988
1987
Minimizing multimodal functions of continuous variables with the "simulated annealing" algorithm.
ACM Trans. Math. Softw., 1987
Proceedings of the Supercomputing, 1987
1986
Caltech Hypercube MIMD Computer Performances Measurements in a Physical Mathematical Application.
Proceedings of the CONPAR 86: Conference on Algorithms and Hardware for Parallel Processing, 1986