The Learnable Evolution Model (LEM) involves alternating periods of optimization and learning, performa extremely well on a range of problems, a specialises in achieveing good resu...
Data discretization is defined as a process of converting continuous data attribute values into a finite set of intervals with minimal loss of information. In this paper, we prove...
In this paper we initiate the study of discrete random variables over domains. Our work is inspired by work of Daniele Varacca, who devised indexed valuations as models of probabi...
—Representative surface reconstruction algorithms taking a gradient field as input enforces the integrability constraint in a discrete manner. While enforcing integrability allo...
We consider a variation of the chip-firing game in a induced subgraph S of a graph G. Starting from a given chip configuration, if a vertex v has at least as many chips as its deg...