Adaptation techniques based on importance weighting were shown effective for RankSVM and RankNet, viz., each training instance is assigned a target weight denoting its importance to the target domain and incorporated into loss functions. In this work, we extend RankBoost using importance weighting framework for ranking adaptation. We find it non-trivial to incorporate the target weight into the...

This research provided the study of importance of factors affecting the decision making of out-sourcing & supplier performance in Textiles domain. The textile market of USA is the scope of this research. The basis of this study allowed comprehending the importance / weight of fac tors of out-sourcing (including Delivery, Flexibility, Cost, Quality & Reliability) varied according to the buyers n...

The success of the convolutional neural network (CNN) comes with a tremendous growth diverse CNN structures, making it hard to deploy on limited-resource platforms. These over-sized models contain large amount filters in layers, which are responsible for almost 99% computation. key question here arises: Do we really need all those filters? By removing entire filters, computational cost can be s...