Participatory budgeting (PB) is a voting paradigm for distributing a divisible resource, usually called a budget, among a set of projects by aggregating the preferences of individuals over these projects. It is implemented ...

Deploying deep learning models in critical areas where the cost of making a wrong decision leads to a substantial financial loss, like in the banking domain, or even loss of life, like in the medical field, is significantly ...

Deep neural networks are the most widely used examples of sophisticated mapping functions from feature space to class labels. In the recent years, several high impact decisions in domains such as finance, healthcare, law ...

Networks are ubiquitous. We start our technical work in this thesis by exploring the classical concept of node centrality (also known as influence measure) in information networks. Like clustering, node centrality is also ...

Reinforcement Learning (RL) serves as a foundational framework for addressing sequential decision-making problems under uncertainty. In recent years, extensive research in this domain has led to significant advancements ...