Real-world systems consisting of interacting entities can be effectively represented as time-evolving networks or graphs, where the entities are depicted as nodes, and the interactions between them are represented as ...

Online decision-making under uncertainty is a fundamental aspect of numerous real-world problems across various domains, including online resource allocation, crowd-sourcing, and online advertising. Multi-Armed Bandits ...

Boolean Functional Synthesis (BFS) is a well-known challenging problem in the domain of automated program synthesis from logical specifications. This problem aims to synthesize a Boolean function that is correct-by-construction ...

Even in the era of Deep Learning based methods, traditional machine learning methods with large data sets continue to attract significant attention. However, we find an apparent lack of a detailed performance characterization ...

This thesis is devoted to designing efficient optimization algorithms for machine learning (ML) problems where the underlying objective function to be optimized is convex but not necessarily differentiable. Such non-smooth ...

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 ...

Deep learning is rapidly integrated into different applications, from medical imaging to financial products. Organisations are spending enormous financial resources to train deep learning models. Often, many organisations ...