In this paper, we develop a new "robust mixing" framework for reasoning about adversarially modified Markov Chains (AMMC). Let P be the transition matrix of an irreducib...
In this paper, we address the modeling and analysis issues associated with a generic theater level campaign where two adversaries pit their military resources against each other ov...
Debasish Ghose, M. Krichman, Jason L. Speyer, Jeff...
We construct machine learned regressors to predict the behaviour of DNA sequencing data from the fluorescent labelled Sanger method. These predictions are used to assess hypothes...
Background -: The availability of multiple whole genome sequences has facilitated in silico identification of fixed and polymorphic transposable elements (TE). Whereas polymorphic...
We show that the mistake bound for predicting the nodes of an arbitrary weighted graph is characterized (up to logarithmic factors) by the cutsize of a random spanning tree of the...