Relying on the truth that not all inputs require the same level of computational cost to
produce reliable predictions, multi-exit networks are gaining attention as a prominent …

Background Data privacy is one of the biggest challenges for any organisation which
processes personal data, especially in the area of medical research where data include …

We present an efficient algorithm for finding k nearest neighbors of a query line segment
among a set of points distributed arbitrarily on a two dimensional plane. Along the way to …

A line is sought in the plane which minimizes the sum of the k largest (Euclidean) weighted
distances from n given points. This problem generalizes the known straight-line center and …

Machine learning (ML) has made huge progress in the last decade and has been applied to
a wide range of critical applications. However, driven by the increasing adoption of machine …

Group nearest group query (GNG for short) is an important variant of NN search. Let D be
the d-multi-dimensional object set, GQ⟨ k, Q⟩ be a GNG with Q containing a set of d-multi …

Current machine learning systems offer great predictive power but also require significant
computational resources. As a result, the promise of a class of optimized machine learning …

The changing nature of healthcare has created a demand for new tools to support both
seekers and providers of medical services in order to ensure that the optimal delivery of care …

In the field of search algorithms, choosing an optimal partition that takes much less time to
search a desired element in an array in comparison with other partitions is a daunting task …

Given a set S of weighted points in the plane, we consider two problems dealing with planar
lines in ℝ 2 under the weighted Euclidean distance:(1) Preprocess S into a data structure …