Colloquium

The nearest-neighbor search (NN) is a classic problem in computer science with vast applications in computer vision. Given a database of points in ${\mathbb R}^d$ and a query point, NN search tries to obtain the data point closest to the query point under some metric distance. However, in many settings such searches are known to suffer from the notorious curse of dimensionality, where running time grows exponentially with $d$ (in optimized solutions). This causes severe performance degradation when working in high-dimensional spaces.

In distributed storage systems (DSS) data is stored over a network of nodes in such a way that a user can retrieve the stored data even if some nodes fail. To achieve such resilience against node failures, DSS introduce data redundancy based on different coding techniques. For example, erasure codes are widely used in such systems. When a single node fails, the system reconstructs the data stored in the failed node to keep the required level of redundancy. This process of data reconstruction for a failed node is called a node repair process.

Education is increasingly mediated by technology, and is used by a wide array of learners from different age groups, socio-economic backgrounds and cultures. The proliferation of educational software provides new opportunities for using computational methods to support students in their learning process and teachers and researchers in their understanding of how students learn. This talk will identify several computational challenges within this context and present some initial solutions that synthesise approaches from artificial intelligence, HCI and data mining.

Secure Multi-party Computation (MPC) is one of the foundational achievements of modern cryptography, allowing multiple, distrusting, parties to jointly compute a function of their inputs, while revealing nothing but the output of the function.
Over the past two decades, the study of MPC has expanded to consider a wide variety of questions, including variants in the attack model, underlying assumptions, complexity and composability of the resulting protocols.