Continuous innovations profoundly impact the financial and commercial domains, reshaping
conventional business practices. Among the disruptive forces, artificial intelligence (AI) …

End-to-end multi-task dialogue systems are usually designed with separate modules for the
dialogue pipeline. Among these, the policy module is essential for deciding what to do in …

For Music Information Retrieval (MIR) downstream tasks, the most common audio
representation is time-frequency-based, such as Mel spectrograms. In order to identify …

When managing an organization, planners often encounter numerous challenging
scenarios. In such instances, relying solely on intuition or managerial experience may not …

As Deep Learning (DL) continues to be widely adopted, the growing field of study on the
robustness of DL approaches in finance is gaining steam. This paper investigates the …

Machine Learning (ML) with distributed privacy preservation is growing in significance as it
focuses on facilitating multi-party learning without requiring actual data sharing. This is …

Federated Learning (FL) presents a novel approach within the domain of Machine Learning
(ML)—enabling the training of ML models in a distributed manner. This paradigmatic shift …

In this study, the method used involves segmenting images into fixed-sized square regions
called superpixels and then analyzing features of each superpixels to determine whether it …

Inflation, or the increase in prices of goods and services, has become a significant issue
during the Covid-19 pandemic. I explore diverse Machine Learning techniques to forecast …

This study examines the fundamental theory necessary for comprehending Variational
Autoencoders (VAEs) and generative latent time-series models. We will also explain how …