Alnur Ali

Experiments with Kemeny ranking: What works when?

This paper performs a comparison of several methods for Kemeny rank aggregation (104 algorithms and combinations thereof in total) originating in social choice theory, machine learning, and theoretical computer science, with the goal of establishing the best trade-offs between search time and performance. We find that, for this theoretically NP-hard task, in practice the problems span three regimes: strong consensus, weak consensus, and no consensus. We make specific recommendations for each, and propose a computationally fast test to distinguish between the regimes.

Cost function minimization in RC ladder networks

For a canonic RC ladder network realized from specified two-port parameters, a proper transformation is applied so as to generate a family of equivalent networks in which the total resistance, total capacitance, and the gain vary continuously with respect to a single variable. A straightforward method is subsequently developed for the minimization of the cost function which combines the above three components with weighting factors.