We propose a rank-k variant of the classical Frank-Wolfe algorithm to solve convex optimization over a trace-norm ball. Our algorithm replaces the top singular-vector computation (1-SVD) in Frank-Wolfe with a top-k singular-vector computation (k-SVD), which can be done by repeatedly applying 1-SVD k times. Our algorithm has a linear convergence rate when the objective function is smooth and str...

Conventional frequent pattern mining algorithms require some user-specified minimum support, and then mine frequent patterns with support values that are higher than the minimum support. As it is difficult to predict how many frequent patterns will be mined with a specified minimum support, the Top-k mining concept has been proposed. The Top-k Mining concept is based on an algorithm for mining ...

The general problem of answering top-k queries can be modeled using lists of objects sorted by their local scores. Fagin et al. proposed the “middleware cost” for a top-k query algorithm, and proposed the efficient sequential Threshold Algorithm (TA). However, since the size of the dataset can be incredible huge, the middleware cost of sequential TA may be intolerable. So, in this paper, we pro...

In this paper, we introduce a new problem, called Top-k SAT, that consists in enumerating the Top-k models of a propositional formula. A Top-k model is defined as a model with less than k models preferred to it with respect to a preference relation. We show that Top-k SAT generalizes two well-known problems: the partial Max-SAT problem and the problem of computing minimal models. Moreover, we p...

Top-k queries have attracted interest in many different areas like network and system monitoring, information retrieval, sensor networks, and so on. Since today many applications issue top-k queries on distributed and outsourced databases, authentication of top-k query results becomes more important. This paper addresses the problem of authenticated top-k aggregation queries (e.g. “find the k o...

optimization of structures for minimum weight has become important in the recent designs. in this study, a genetic optimization algorithm for weight minimization of steel frames has been used. the genetic algorithm is an optimization and search technique based on the principles of genetics and natural selection. constraints regarding material strength and serviceability are taken from “aisc cod...