In this paper, a general framework for the analysis of a connection between the training of artificial neural networks via the dynamics of Markov chains and the approximation of c...
Many nonlinear dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
In this paper, we propose a novel on-chip voltage drop reduction technique for on-chip power delivery networks of VLSI systems in the presence of variational leakage current sourc...
We present a novel technique to exploit the power-performance tradeoff. The technique can be used stand-alone or in conjunction with dynamic voltage scaling, the mainstream techn...
Fitting data by a bounded complexity linear model is equivalent to low-rank approximation of a matrix constructed from the data. The data matrix being Hankel structured is equival...