This dissertation investigates how modern machine learning (ML) methods, with a particular focus on multi-task learning (MTL) frameworks, can enhance forecasts in financial and macroeconomic contexts. Chapter 1 outlines the limitations of traditional econometr…
Magistrsko delo obravnava področje analize sentimenta z uporabo strojnega učenja in obdelave naravnega jezika. Namen dela je razviti model, ki bi bil sposoben analizirati sentiment besedil, pridobljenih s spletnih platform, zlasti z družbenega omrežja X (prej…
The widespread adoption of deep learning has led to a surge in demand for the efficient deployment of Deep Neural Networks (DNNs) on embedded and resource-constrained systems. These platforms are increasingly tasked with performing complex inference workloads…
The proliferation of user-generated content on online platforms like Reddit has created vast datasets that can be used to extract significant knowledge, such as author attribution through various analytical techniques. Author attribution is the task of identif…
El Reconocimiento de Acciones Humanas en videos (HAR) consiste en identificar y clasificar diferentes acciones que involucran una o más personas. Este campo continúa en desarrollo ya que los resultados aún no alcanzan niveles satisfactorios para muchas de sus…
Η Επεξεργασία Φυσικής Γλώσσας (NLP) για επιχειρηματικά και χρηματοοικονομικά κείμενα (Hahn et al., 2018; Chen et al., 2022) αποτελεί ένα ταχέως αναπτυσσόμενο ερευνητικό πεδίο που εφαρμόζει υπολογιστικές τεχνικές σε κείμενα όπως εταιρικά έγγραφα, αναφορές αναλυ…
Inventory management and operation planning in retail sector involve accurate demand forecasting as a key element of the process. Linear models and tree-based models are typical examples of traditional forecasting models that may not work well in capturing com…
Hava kirliliği, PM10 gibi partikül madde içeren yanma gazlarının salınması sonucu ortaya çıkmaktadır. Doğru ve güvenilir teknikler ile PM10 konsantrasyonlarının tahmini, sağlık risklerini düşürmek için göz önüne alınmalıdır. Ortam hava kalitesi ve halk sağlığı…
This study aims to apply Natural Language Processing (NLP) and develop Machine Learning algorithms for detecting hate speech in social media. The “Hate Speech and Offensive Language dataset” is used, which comprises 24,783 manually annotated English tweets lab…
The adoption of network virtualization and cloud computing has introduced new complexities and attack vectors, which demands more intelligent and scalable security solutions. In such cases, traditional Intrusion Detection Systems (IDS) often have struggle to p…
This dissertation consists of three essays on forecasting time series with machine learning techniques, delving into different financial and economic domains.The first essay investigates the forecasting accuracy of the S&P 500 stock market index during the pan…
In-Context Learning describes a form of learning that occurs when a model accumulates information in its context or memory. For example, a Long Short-Term Memory unit (LSTM) can rapidly adapt to a novel task as input/target exemplars are fed into it. While in-…
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