Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

The Bodossaki Foundation announced two distinguished Greek scientists honored for their pioneering, internationally ...

This paper studies online distributionally robust Markov games with linear function approximation. It is the first to identify the hardness of learning in this setting, and proposes the DR-CCE-LSI ...

Abstract: In this article we study a generalized team orienteering problem (GTOP), which is to find service paths for multiple homogeneous vehicles in a network such that the profit sum of serving the ...

The area of approximation algorithms is aimed at giving provable guarantees on the performance of heuristics for hard problems. The course will present general techniques (such as convex ...

Timely reconstruction of epidemic dynamics is essential for public health, and structured coalescent models constitute an essential tool for this purpose. However, statistical and computational ...

First-order derivatives: n additional function calls are needed. Second-order derivatives based on gradient calls, when the "grd" module is specified (Dennis and Schnabel 1983): n additional gradient ...

Computing the minimal volume oriented bounding box for a given point cloud in 3D is a hard problem in computer science. Exact algorithms are known and of cubic order in the number of points in 3D. A ...

Abstract: Compressive sensing (CS) states that a sparse signal can be recovered from a small number of linear measurements, and that this recovery can be performed efficiently in polynomial time. The ...