In this paper, we propose a method for ranking fashion images to find the ones which might be liked by more people. We collect two new datasets from image sharing websites (Pinterest and Polyvore). We represent fashion images based on attributes: semantic attributes and data-driven attributes. To learn semantic attributes from limited training data, we use an algorithm on multi-task convolution...

In this paper, we present a new type of multi-class learning algorithm called a linear-max algorithm. Linear-max algorithms learn with a special type of attribute called a sub-expert. A sub-expert is a vector attribute that has a value for each output class. The goal of the multi-class algorithm is to learn a linear function combining the sub-experts and to use this linear function to make corr...

this paper addresses a multi-criteria decision based methodology to develop a road network cost function for route finding analysis in a geographic information system (gis). over the years, several studies relating to route planning process in gis and intelligent transportation systems (its) have been conducted, most of which rely on the use of one-dimensional variables like distance or time as...

A decision aid for osteoarthritis was developed using the best available evidence on effect size, potential harms and self-rated performance for other attributes. The aid was developed using a multi-criteria decision analytic tool capable of combing evidence and an individual's preferences for the attributes related to treatment.