Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...
We present a probabilistic analysis of integer linear programs (ILPs). More specifically, we study ILPs in a so-called smoothed analysis in which it is assumed that first an adve...
Gate sizing in VLSI design is a widely-used method for power or area recovery subject to timing constraints. Several previous works have proposed gate sizing heuristics for power ...
A central issue in the design of modern communication networks is that of providing performance guarantees. This issue is particularly important if the networks support real-time t...
We focus on data gathering problems in energy constrained networked sensor systems. The system operates in rounds where a subset of the sensors generate a certain number of data p...