Giorgio Corani

Orcid: 0000-0002-1541-8384

Affiliations:
  • University of Applied Sciences and Arts of Southern Switzerland, Switzerland


According to our database1, Giorgio Corani authored at least 65 papers between 2005 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2024
Efficient probabilistic reconciliation of forecasts for real-valued and count time series.
Stat. Comput., February, 2024

2023
Electricity Load and Peak Forecasting: Feature Engineering, Probabilistic LightGBM and Temporal Hierarchies.
Proceedings of the Advanced Analytics and Learning on Temporal Data, 2023

2022
A Bayesian hierarchical score for structure learning from related data sets.
Int. J. Approx. Reason., 2022

Probabilistic reconciliation of forecasts via importance sampling.
CoRR, 2022

2021
Time Series Forecasting with Gaussian Processes Needs Priors.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2021

State Space Approximation of Gaussian Processes for Time Series Forecasting.
Proceedings of the Advanced Analytics and Learning on Temporal Data, 2021

2020
Correction to: Efficient feature selection using shrinkage estimators.
Mach. Learn., 2020

Automatic Forecasting using Gaussian Processes.
CoRR, 2020

Sampling Subgraphs with Guaranteed Treewidth for Accurate and Efficient Graphical Inference.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Probabilistic Reconciliation of Hierarchical Forecast via Bayes' Rule.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Structure Learning from Related Data Sets with a Hierarchical Bayesian Score.
Proceedings of the International Conference on Probabilistic Graphical Models, 2020

2019
Efficient feature selection using shrinkage estimators.
Mach. Learn., 2019

Special issue on the tenth International Symposium on Imprecise Probability: Theories and Applications (ISIPTA '17).
Int. J. Approx. Reason., 2019

Hierarchical estimation of parameters in Bayesian networks.
Comput. Stat. Data Anal., 2019

Hybrid heuristic for the optimal design of photovoltaic installations considering mismatch loss effects.
Comput. Oper. Res., 2019

2018
Approximate structure learning for large Bayesian networks.
Mach. Learn., 2018

Efficient learning of bounded-treewidth Bayesian networks from complete and incomplete data sets.
Int. J. Approx. Reason., 2018

Entropy-based pruning for learning Bayesian networks using BIC.
Artif. Intell., 2018

2017
Statistical comparison of classifiers through Bayesian hierarchical modelling.
Mach. Learn., 2017

Time for a Change: a Tutorial for Comparing Multiple Classifiers Through Bayesian Analysis.
J. Mach. Learn. Res., 2017

The multilabel naive credal classifier.
Int. J. Approx. Reason., 2017

Hierarchical Multinomial-Dirichlet Model for the Estimation of Conditional Probability Tables.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Improved Local Search in Bayesian Networks Structure Learning.
Proceedings of the 3rd Workshop on Advanced Methodologies for Bayesian Networks, 2017

2016
Should We Really Use Post-Hoc Tests Based on Mean-Ranks?
J. Mach. Learn. Res., 2016

Learning extended tree augmented naive structures.
Int. J. Approx. Reason., 2016

Air pollution prediction via multi-label classification.
Environ. Model. Softw., 2016

Learning Bounded Treewidth Bayesian Networks with Thousands of Variables.
CoRR, 2016

Learning Treewidth-Bounded Bayesian Networks with Thousands of Variables.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
A Bayesian approach for comparing cross-validated algorithms on multiple data sets.
Mach. Learn., 2015

Credal model averaging for classification: representing prior ignorance and expert opinions.
Int. J. Approx. Reason., 2015

Bayesian Hypothesis Testing in Machine Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Learning Bayesian Networks with Thousands of Variables.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

A Bayesian nonparametric procedure for comparing algorithms.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Comments on "Imprecise probability models for learning multinomial distributions from data. Applications to learning credal networks" by Andrés R. Masegosa and Serafín Moral.
Int. J. Approx. Reason., 2014

Credal ensembles of classifiers.
Comput. Stat. Data Anal., 2014

Trading off Speed and Accuracy in Multilabel Classification.
Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

Extended Tree Augmented Naive Classifier.
Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

A Bayesian Wilcoxon signed-rank test based on the Dirichlet process.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
A Bayesian network model for predicting pregnancy after in vitro fertilization.
Comput. Biol. Medicine, 2013

An Ensemble of Bayesian Networks for Multilabel Classification.
Proceedings of the IJCAI 2013, 2013

2012
Evaluating credal classifiers by utility-discounted predictive accuracy.
Int. J. Approx. Reason., 2012

Credal Classification based on AODE and compression coefficients
CoRR, 2012

Likelihood-Based Robust Classification with Bayesian Networks.
Proceedings of the Advances in Computational Intelligence, 2012

Compression-based AODE Classifiers.
Proceedings of the ECAI 2012, 2012

2011
Artificial Defocus for Displaying Markers in Microscopy Z-Stacks.
IEEE Trans. Vis. Comput. Graph., 2011

Improving parameter learning of Bayesian nets from incomplete data
CoRR, 2011

2010
A tree augmented classifier based on Extreme Imprecise Dirichlet Model.
Int. J. Approx. Reason., 2010

3D Localization of Pronuclei of Human Zygotes Using Textures from Multiple Focal Planes.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2010

Blastomere segmentation and 3D morphology measurements of early embryos from hoffman modulation contrast image stacks.
Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010

Restricting the IDM for Classification.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods, 2010

Robust Texture Recognition Using Credal Classifiers.
Proceedings of the British Machine Vision Conference, 2010

Simultaneous Focusing and Contouring of Human Zygotes for in Vitro Fertilization.
Proceedings of the BIOSIGNALS 2010, 2010

2009
Lazy naive credal classifier.
Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data, 2009

Reproducing human decisions in reservoir management: the case of lake Lugano.
Proceedings of the Information Technologies in Environmental Engineering, 2009

Lighting-Aware Segmentation of Microscopy Images for In Vitro Fertilization.
Proceedings of the Advances in Visual Computing, 5th International Symposium, 2009

2008
Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2.
J. Mach. Learn. Res., 2008

JNCC2: An extension of naive Bayes classifier suited for small and incomplete data sets.
Environ. Model. Softw., 2008

Credal Model Averaging: An Extension of Bayesian Model Averaging to Imprecise Probabilities.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

Naive credal classifier 2: an extension of naive Bayes for delivering robust classifications.
Proceedings of The 2008 International Conference on Data Mining, 2008

2006
Prediction of ungulates abundance through local linear algorithms.
Environ. Model. Softw., 2006

VC-dimension and structural risk minimization for the analysis of nonlinear ecological models.
Appl. Math. Comput., 2006

Classification of Dementia Types from Cognitive Profiles Data.
Proceedings of the Knowledge Discovery in Databases: PKDD 2006, 2006

2005
Environmental modelling via learning-from-data techniques.
PhD thesis, 2005

Coupling fuzzy modeling and neural networks for river flood prediction.
IEEE Trans. Syst. Man Cybern. Part C, 2005

An application of pruning in the design of neural networks for real time flood forecasting.
Neural Comput. Appl., 2005


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