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Full-Text Articles in Social and Behavioral Sciences
A Scalable Algorithm For Learning A Mahalanobis Distance Metric, Junae Kim, Chunhua Shen, Lei Wang
A Scalable Algorithm For Learning A Mahalanobis Distance Metric, Junae Kim, Chunhua Shen, Lei Wang
Faculty of Engineering and Information Sciences - Papers: Part A
A distance metric that can accurately re°ect the intrinsic characteristics of data is critical for visual recognition tasks. An e®ective solution to de¯ning such a metric is to learn it from a set of training sam- ples. In this work, we propose a fast and scalable algorithm to learn a Ma- halanobis distance. By employing the principle of margin maximization to secure better generalization performances, this algorithm formulates the metric learning as a convex optimization problem with a positive semide¯nite (psd) matrix variable. Based on an important theorem that a psd matrix with trace of one can always be represented …
A Λ-Cut And Goal-Programming-Based Algorithm For Fuzzy-Linear Multiple-Objective Bilevel Optimization, Ya Gao, Guangquan Zhang, Jun Ma, Jie Lu
A Λ-Cut And Goal-Programming-Based Algorithm For Fuzzy-Linear Multiple-Objective Bilevel Optimization, Ya Gao, Guangquan Zhang, Jun Ma, Jie Lu
Faculty of Engineering and Information Sciences - Papers: Part A
Bilevel-programming techniques are developed to handle decentralized problems with two-level decision makers, which are leaders and followers, who may have more than one objective to achieve. This paper proposes a λ-cut and goal-programming-based algorithm to solve fuzzy-linear multiple-objective bilevel (FLMOB) decision problems. First, based on the definition of a distance measure between two fuzzy vectors using λ-cut, a fuzzy-linear bilevel goal (FLBG) model is formatted, and related theorems are proved. Then, using a λ-cut for fuzzy coefficients and a goal-programming strategy for multiple objectives, a λ-cut and goal-programming-based algorithm to solve FLMOB decision problems is presented. A case study for …