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This project aims to investigate the possibility of exploiting the polarimetric radar measurements to improve the discrimination between hail stones of different size, by involving machine learning techniques. ...
The temperature and pressure dependence of structural phase transitions determine the structure-functionality relationships in many technologically important materials. Harmonic Hamiltonians have proven successful in predicting the vibrational properties o ...
Electromagnetic Time Reversal (EMTR) has been used to locate different types of electromagnetic sources. We propose a novel technique based on the combination of EMTR and Machine Learning (ML) for source localization. We show for the first time that ML tec ...
Games with continuous strategy sets arise in several machine learning problems (e.g. adversarial learning). For such games, simple no-regret learning algorithms exist in several cases and ensure convergence to coarse correlated equilibria (CCE). The effic ...
In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. Thisidentifica ...
High levels of cognitive workload decreases human's performance and leads to failures with catastrophic outcomes in risky missions. Today, reliable cognitive workload detection presents a common major challenge, since the workload is not directly observabl ...
In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...
In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...
The area of privacy preserving machine learning has been of growing importance in practice, which has lead to an increased interest in this topic in both academia and industry. We have witnessed this through numerous papers and systems published and develo ...