Multi-task learning (MTL) has been shown to improve prediction performance in a number of different contexts by learning models jointly on multiple different, but related tasks. Network data, which are a priori data with a rich relational structure, provide an important context for applying MTL. In particular, the explicit relational structure implies that network data is not i.i.d. data. Netwo...

Routing metrics of multi-hop wireless networks differ from traditional routing metrics due to dynamic and unpredictable nature of wireless media. Many routing metrics were proposed for single-radio as well as multi-radio mesh networks. In this paper we study various routing metrics such as Expected Transmission Count (ETX) metric, Expected Transmission Time (ETT), Weighted cumulative ETT (WCETT...

Image fusion is defined as the process of combining two or more different images into a new single image retaining important features from each image with extended information content. There are two approaches to image fusion, namely Spatial Fusion and Transform fusion. In Spatial fusion, the pixel values from the source images are directly summed up and taken average to form the pixel of the c...

This paper investigates the properties of the widely-utilized F1 metric as used to evaluate the performance of multi-label classifiers. We show that given an uninformative binary classifier, F1-optimal thresholding is to predict all instances positive. More surprisingly, we prove a relationship between the optimal threshold and the best achievable F1 score over all thresholds. We demonstrate th...

BackgroundMalnourishment is associated with poor outcomes after lung transplantation. Validated screening tools for patients awaiting transplants are needed. We assessed the association of Nutritional Risk Index (NRI) transplantation.MethodsWe categorized adult (aged more than 18 years) undergoing incident transplantation in Scientific Registry Transplant Recipients between 2005 and 2018 (n = 1...

introduction: appropriate definition of the distance measure between diffusion tensors has a deep impact on diffusion tensor image (dti) segmentation results. the geodesic metric is the best distance measure since it yields high-quality segmentation results. however, the important problem with the geodesic metric is a high computational cost of the algorithms based on it. the main goal of this ...

Nearest neighbor classifier is a widely-used effective method for multi-class problems. However, it suffers from the problem of the curse of dimensionality in high dimensional space. To solve this problem, many adaptive nearest neighbor classifiers were proposed. In this paper, a locally adaptive nearest neighbor classification method based on supervised learning style which works well for the ...

In this paper, we establish a fixed point theorem for multi-valued operators in a complete b−metric space using the concept of Berinde and Berinde [9] on multi-valued weak contractions for the Picard iteration in a metric space. Our main result generalizes, extends and improves some of the recent results of Berinde and Berinde [9] as well as those of Daffer and Kaneko [17] and also unifies seve...

Similarity retrieval is an important paradigm for searching in environments where exact match has little meaning. Moreover, in order to enlarge the set of data types for which the similarity search can efficiently be performed, the notion of mathematical metric space provides a useful abstraction for similarity. In this paper we consider the problem of organizing and searching large data-sets f...