We present a fast non-iterative method for approximating the leading eigenvector so as to render graph-spectral based grouping algorithms more efficient. The approximation is base...
Antonio Robles-Kelly, Sudeep Sarkar, Edwin R. Hanc...
We examine the theoretical and numerical global convergence properties of a certain "gradient free" stochastic approximation algorithm called the "simultaneous pertu...
In many pattern recognition/classification problem the true class conditional model and class probabilities are approximated for reasons of reducing complexity and/or of statistic...
This work investigates a geometric approach to proving cell probe lower bounds for data structure problems. We consider the approximate nearest neighbor search problem on the Bool...
We investigate the problem of finding an unknown cut through querying vertices of a graph G. Our complexity measure is the number of submitted queries. To avoid some worst cases, ...