Reinforcement Learning (RL) has progressed from simple control tasks to complex real-world challenges with large state spaces. During initial iterations of training in most Reinforcement Learning (RL) algorithms, agents ...

The problem of feature selection is critical in several areas of machine learning and data analysis such as, for example, cancer classification using gene expression data, text categorization, etc. In this work, we consider ...

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 ...

Let F be a family of sets. A graph G is an intersection graph of sets from the family F if there exists a mapping f : V (G)→ F such that, An interval graph is an intersection graph of a family of closed intervals on the ...

A large number of mathematical models in engineering and physical sciences employ Partial Differential Equations (PDEs). The sheer number of operations required in numerically integrating PDEs in these applications has ...

Websites are shifting from static model to dynamic model, in order to deliver their users with dynamic, interactive, and personalized experiences. However, dynamic content generation comes at a cost – each request ...

We provide two static analysis approaches(using theorem proving) that check if a given (recursive) procedure behaves as if it were stateless, even when it maintains state in global variables. In other words, we check if ...

The problem of identifying clusters arising in the context of topic models and related approaches is important in the area of machine learning. The problem concerning traversals on Concept Association Networks is of great ...

This thesis investigates some combinatorial problems arising in quantum physics and model counting. In particular, we develop new graph-theoretic techniques to resolve some open questions from quantum photonics. We also ...