Sotirios Chatzis
Orcid: 0000-0002-4956-4013
According to our database1,
Sotirios Chatzis
authored at least 110 papers
between 2006 and 2024.
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Bibliography
2024
Continual Deep Learning on the Edge via Stochastic Local Competition among Subnetworks.
CoRR, 2024
2023
Continuous authentication with feature-level fusion of touch gestures and keystroke dynamics to solve security and usability issues.
Comput. Secur., September, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
A New Dataset for End-to-End Sign Language Translation: The Greek Elementary School Dataset.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
2022
Rethinking Bayesian Learning for Data Analysis: The art of prior and inference in sparsity-aware modeling.
IEEE Signal Process. Mag., 2022
Key factors driving the adoption of behavioral biometrics and continuous authentication technology: an empirical research.
Inf. Comput. Secur., 2022
BioGames: a new paradigm and a behavioral biometrics collection tool for research purposes.
Inf. Comput. Secur., 2022
Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-Learning.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the 3rd ACM International Conference on AI in Finance, 2022
Competing Mutual Information Constraints with Stochastic Competition-Based Activations for Learning Diversified Representations.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Re-constructing the interbank links using machine learning techniques. An application to the Greek interbank market.
Intell. Syst. Appl., 2021
Inf. Fusion, 2021
CoRR, 2021
Proceedings of the Speech and Computer - 23rd International Conference, 2021
Stochastic Transformer Networks with Linear Competing Units: Application to end-to-end SL Translation.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
Knowl. Based Syst., 2020
CoRR, 2020
Variational Conditional-Dependence Hidden Markov Models for Human Action Recognition.
CoRR, 2020
Variational Bayesian Sequence-to-Sequence Networks for Memory-Efficient Sign Language Translation.
Proceedings of the Advances in Visual Computing - 15th International Symposium, 2020
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Proceedings of the ICAIF '20: The First ACM International Conference on AI in Finance, 2020
2019
IEEE Trans. Neural Networks Learn. Syst., 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
2018
Leveraging Statistical Machine Learning to Address Failure Localization in Optical Networks.
JOCN, 2018
Latent subspace modeling of sequential data under the maximum entropy discrimination framework.
Neurocomputing, 2018
Expert Syst. Appl., 2018
Forecasting stock market crisis events using deep and statistical machine learning techniques.
Expert Syst. Appl., 2018
Proceedings of the 2018 IEEE Security and Privacy Workshops, 2018
On learning bandwidth allocation models for time-varying traffic in flexible optical networks.
Proceedings of the 2018 International Conference on Optical Network Design and Modeling, 2018
Charging Policies for PREYs used for Service Delivery: A Reinforcement Learning Approach.
Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018
A Recurrent Latent Variable Model for Supervised Modeling of High-Dimensional Sequential Data.
Proceedings of the 2018 Innovations in Intelligent Systems and Applications, 2018
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018
2017
Performance Analysis of a Data-Driven Quality-of-Transmission Decision Approach on a Dynamic Multicast-Capable Metro Optical Network.
JOCN, 2017
A hidden Markov model with dependence jumps for predictive modeling of multidimensional time-series.
Inf. Sci., 2017
Expert Syst. Appl., 2017
Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems, 2017
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017
Proceedings of the 2017 International Conference on Optical Network Design and Modeling, 2017
A Variational Recurrent Neural Network for Session-Based Recommendations using Bayesian Personalized Ranking.
Proceedings of the Information Systems Development: Advances in Methods, Tools and Management, 2017
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
2016
Software defect prediction using doubly stochastic Poisson processes driven by stochastic belief networks.
J. Syst. Softw., 2016
A Nonstationary Hidden Markov Model with Approximately Infinitely-Long Time-Dependencies.
Int. J. Artif. Intell. Tools, 2016
Expert Syst. Appl., 2016
A data-driven QoT decision approach for multicast connections in metro optical networks.
Proceedings of the 2016 International Conference on Optical Network Design and Modeling, 2016
Users' Attitudes on Mobile Devices: Can Users' Practices Protect their Sensitive Data?
Proceedings of the 10th Mediterranean Conference on Information Systems, 2016
2015
IEEE Trans. Neural Networks Learn. Syst., 2015
IEEE Trans. Neural Networks Learn. Syst., 2015
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015
A Nonparametric Bayesian Approach toward Stacked Convolutional Independent Component Analysis.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015
Inducing Space Dirichlet Process Mixture Large-Margin Entity RelationshipInference in Knowledge Bases.
Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015
2014
IEEE Trans. Pattern Anal. Mach. Intell., 2014
A Nonparametric Bayesian Approach Toward Stacked Convolutional Independent Component Analysis.
CoRR, 2014
Proceedings of the 18th Panhellenic Conference on Informatics, 2014
A Partially-Observable Markov Decision Process for Dealing with Dynamically Changing Environments.
Proceedings of the Artificial Intelligence Applications and Innovations, 2014
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014
2013
A conditional random field-based model for joint sequence segmentation and classification.
Pattern Recognit., 2013
A Markov random field-regulated Pitman-Yor process prior for spatially constrained data clustering.
Pattern Recognit., 2013
IEEE Trans. Pattern Anal. Mach. Intell., 2013
A latent variable Gaussian process model with Pitman-Yor process priors for multiclass classification.
Neurocomputing, 2013
Corrigendum to "Maximum-margin classification of sequential data with infinitely-long temporal dependencies" [Expert Systems with Applications 40 (11) (2013) 4519-4527].
Expert Syst. Appl., 2013
Margin-maximizing classification of sequential data with infinitely-long temporal dependencies.
Expert Syst. Appl., 2013
Proceedings of the 30th International Conference on Machine Learning, 2013
Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013
2012
IEEE Trans. Robotics, 2012
IEEE Trans. Neural Networks Learn. Syst., 2012
Visual Workflow Recognition Using a Variational Bayesian Treatment of Multistream Fused Hidden Markov Models.
IEEE Trans. Circuits Syst. Video Technol., 2012
Robotics Auton. Syst., 2012
Pattern Recognit., 2012
Proceedings of the 4th Asian Conference on Machine Learning, 2012
Expert Syst. Appl., 2012
A sparse nonparametric hierarchical Bayesian approach towards inductive transfer for preference modeling.
Expert Syst. Appl., 2012
A Mixture Gaussian Process Conditional Heteroscedasticity Model with Power-Law Nature
CoRR, 2012
Proceedings of the Artificial Intelligence Applications and Innovations, 2012
2011
A variational Bayesian methodology for hidden Markov models utilizing Student's-t mixtures.
Pattern Recognit., 2011
Expert Syst. Appl., 2011
A fuzzy c-means-type algorithm for clustering of data with mixed numeric and categorical attributes employing a probabilistic dissimilarity functional.
Expert Syst. Appl., 2011
Deformable probability maps: Probabilistic shape and appearance-based object segmentation.
Comput. Vis. Image Underst., 2011
Proceedings of the IEEE 23rd International Conference on Tools with Artificial Intelligence, 2011
2010
IEEE Trans. Pattern Anal. Mach. Intell., 2010
Fuzzy Sets Syst., 2010
Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010
2009
Factor Analysis Latent Subspace Modeling and Robust Fuzzy Clustering Using t -Distributions.
IEEE Trans. Fuzzy Syst., 2009
IEEE Trans. Pattern Anal. Mach. Intell., 2009
2008
Signal Modeling and Classification Using a Robust Latent Space Model Based on t Distributions.
IEEE Trans. Signal Process., 2008
A Fuzzy Clustering Approach Toward Hidden Markov Random Field Models for Enhanced Spatially Constrained Image Segmentation.
IEEE Trans. Fuzzy Syst., 2008
Pattern Recognit. Lett., 2008
Future Gener. Comput. Syst., 2008
A robust approach towards sequential data modeling and its application in automatic gesture recognition.
Proceedings of the IEEE International Conference on Acoustics, 2008
2007
A content-based image retrieval scheme allowing for robust automatic personalization.
Proceedings of the 6th ACM International Conference on Image and Video Retrieval, 2007
2006
Video Representation and Retrieval Using Spatio-temporal Descriptors and Region Relations.
Proceedings of the Artificial Neural Networks, 2006
A Cross Media Platform for Personalized Leisure & Entertainment: The POLYMNIA Approach.
Proceedings of the Second International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution, 2006