Reinforcement learning (RL) in real world applications faces major hurdles - the foremost being safety of the physical system controlled by the learning agent and the varying environment conditions in which the autonomous ...

Secure Multi-party Computation (MPC) with small population has drawn focus specifically due to customization in techniques and resulting efficiency that the constructions can offer. Practically efficient constructions ...

Stochastic approximation algorithms are sequential non-parametric methods for finding a zero or minimum of a function in the situation where only the noisy observations of the function values are available. Two time-scale ...

Personalized recommendation systems use the data generated by user-item interactions (for example, in the form of ratings) to predict different users interests in available items and recommend a set of items or products ...

Statically verifying behavioral properties of programs is an important research problem. An efficient solution to this problem will have visible effects over multiple domains, ranging from program development, program ...

Web-based applications and distributed systems are ubiquitous and indispensable today. These systems use multiple parallel machines for greater functionality, and efficient and reliable computation. At the same time they ...

State of the art in high-performance deep learning is primarily driven by highly tuned libraries. These libraries are often hand-optimized and tuned by expert programmers using low-level abstractions with significant effort. ...

Databases are central to the functioning of most IT-enabled processes and services. In many domains, databases are accessed and updated via applications written in general-purpose lan- guages, as such applications need ...

In the modern era of computing, machine learning tools have demonstrated their potential in vital sectors, such as healthcare and finance, to derive proper inferences. The sensitive and confidential nature of the data in ...

Graphs have been extensively used for modelling real-world network datasets, however, they are restricted to pairwise relationships, i.e., each edge connects exactly two vertices. Hypergraphs relax the notion of edges ...