In the recent decade, deep learning techniques have been widely adopted for founding
artificial Intelligent applications, which led to successes in many data analysis tasks, such as …

This article develops a cloud-based protocol for a constrained quadratic optimization
problem involving multiple parties, each holding private data. The protocol is based on the …

Cloud computing enables an economically promising paradigm of computation outsourcing.
However, how to protect customers confidential data processed and generated during the …

With cloud computing and mobile computing becoming more and more popular, there are a
lot potential applications for computation outsourcing to the cloud. This paper investigates …

This paper considers a distributed multi-agent optimization problem, with the global
objective consisting of the sum of local objective functions of the agents. The agents solve …

Cryptographic solutions to privacy-preserving multiparty linear programming are slow. This
makes them unsuitable for many economically important applications, such as supply chain …

The assignment problem is an essential problem in many application fields and frequently
used to optimize resource usage. The problem is well understood and various efficient …

We describe a framework for randomized unit testing, and give empirical evidence that
generating unit test cases randomly and then minimizing the failing test cases results in …

To date, increasing number of entities on the smart grid begin to establish their local energy
generator for ensuring reliability and resilience of power supply. These 'microgrids' can …

Secure multiparty computation is a basic concept of growing interest in modern
cryptography. It allows a set of mutually distrusting parties to perform a computation on their …