Michele Donini

According to our database1, Michele Donini authored at least 25 papers between 2014 and 2019.

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Bibliography

2019
Combining heterogeneous data sources for neuroimaging based diagnosis: re-weighting and selecting what is important.
NeuroImage, 2019

Taking Advantage of Multitask Learning for Fair Classification.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018
Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels.
IEEE Trans. Neural Netw. Learning Syst., 2018

Scuba: scalable kernel-based gene prioritization.
BMC Bioinformatics, 2018

Empirical Risk Minimization Under Fairness Constraints.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Emerging trends in machine learning: beyond conventional methods and data.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Voting with Random Neural Networks: a Democratic Ensemble Classifier.
Proceedings of the RiCeRcA Workshop co-located with the 17th International Conference of the Italian Association for Artificial Intelligence, 2018

2017
Learning deep kernels in the space of dot product polynomials.
Machine Learning, 2017

Measuring the expressivity of graph kernels through Statistical Learning Theory.
Neurocomputing, 2017

A Speaker Adaptive DNN Training Approach for Speaker-Independent Acoustic Inversion.
Proceedings of the Interspeech 2017, 2017

Forward and Reverse Gradient-Based Hyperparameter Optimization.
Proceedings of the 34th International Conference on Machine Learning, 2017

On Hyperparameter Optimization in Learning Systems.
Proceedings of the 5th International Conference on Learning Representations, 2017

Learning dot-product polynomials for multiclass problems.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Fast hyperparameter selection for graph kernels via subsampling and multiple kernel learning.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

2016
Stairstep recognition and counting in a serious Game for increasing users' physical activity.
Personal and Ubiquitous Computing, 2016

A multimodal multiple kernel learning approach to Alzheimer's disease detection.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Distributed variance regularized Multitask Learning.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Measuring the Expressivity of Graph Kernels through the Rademacher Complexity.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Advances in Learning with Kernels: Theory and Practice in a World of growing Constraints.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015
EasyMKL: a scalable multiple kernel learning algorithm.
Neurocomputing, 2015

Multiple Graph-Kernel Learning.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2015

Feature and kernel learning.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014
ClimbTheWorld: real-time stairstep counting to increase physical activity.
Proceedings of the 11th International Conference on Mobile and Ubiquitous Systems: Computing, 2014

Learning Anisotropic RBF Kernels.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

Easy multiple kernel learning.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014


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