Deep neural network-based models have achieved unprecedented performance levels over many tasks in the traditional supervised setting and scale well with large quantities of data. On the other hand, improving performance ...

Graph processing at scales of millions-billions of vertices and edges has become common to solve real-world problems in domains like social networks, smart cities and genomics. Distributed "Big Data" platforms for graph ...

Counter systems are a well-known and powerful modeling notation for specifying infnite state systems. In this thesis we target the problem of checking temporal properties of counter systems. We address three predominant ...

In this thesis, we focus on the problem of program debugging and present novel deep learning based techniques for bug-localization and program repair. Deep learning techniques have been successfully applied to a variety ...

Abstract In recent years, deep neural networks have achieved extraordinary performance on supervised learning tasks. Convolutional neural networks (CNN) have vastly improved the state of the art for most computer vision ...

In secure multi-party computation (MPC), n parties wish to jointly perform a computation on their private inputs in a secure way, so that no adversary corrupting a subset of the parties can learn more information than their ...

The very thought about “relating” objects makes us assume the relation would be “pairwise”, and not of a “higher-order” — involving possibly more than two of them at a time. Yet in reality, higher-order relations do exist ...

Consider the problem of Polynomial Identity Testing(PIT): we are given an arithmetic circuit computing a multivariate polynomial over some eld and we have to determine whether that polynomial is identically zero or not. ...

The correctness of hard real-time systems depends not only on its logical correctness but also, on its ability to meet all its deadline. Existing real-time systems use either a pure real-time scheduler or a real-time ...

Acyclic path profile is an abstraction of dynamic control flow paths of procedures and has been found to be useful in a wide spectrum of activities. Unfortunately, the runtime overhead of obtaining such a profile can be ...