There is growing interest in algorithms for processing and querying continuous data streams (i.e., data that is seen only once in a fixed order) with limited memory resources. Pro...
Sumit Ganguly, Minos N. Garofalakis, Amit Kumar, R...
This paper considers the problem of Bayesian inference in dynamical models with time-varying dimension. These models have been studied in the context of multiple target tracking pr...
Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineeri...
Chaotic iteration sequences is a method for approximating fixpoints of monotonic functions proposed by Patrick and Radhia Cousot. It may be used in specialisation algorithms for ...
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...