Efficient Algorithms for Kernel Aggregation Queries


Kernel functions provide assistance for a wide variety of application types, including those that require activities such as density estimation, classification, regression, or the detection of outliers. When dealing with these types of tasks, one of the online operations that is frequently performed is to compute the weighted aggregation of kernel function values with respect to a set of points. Nevertheless, scalable aggregation methods for typical kernel functions (such as the Gaussian kernel, polynomial kernel, sigmoid kernel, and additive kernels) and weighting schemes have not yet been discovered. In this paper, we present a novel and efficient bounding technique that leverages index structures in order to speed up the computation of kernel aggregation. The technique can be found in the introduction. In addition to this, we extend our method to additive kernel functions such as the JS and Hellinger kernels, the 2 kernel, the intersection kernel, and the JS kernel, which are all widely used in a variety of fields such as computer vision, medical science, and geoscience, amongst others. In order to manage the additive kernel functions, we have further developed the novel and efficient bound functions in order to evaluate the kernel aggregation in the most time-effective manner. Experimentation and research on a large number of real datasets have shown that our proposed solution, KARL, is at least one order of magnitude faster than the current state of the art when it comes to the execution of various kernel function types.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : TARA: An Efficient Random Access Mechanism for NB-IoT by Exploiting TA Value Difference in Collided Preambles ABSTRACT: The 3rd Generation Partnership Project (3GPP) has specified the narrowband Internet of Things
PROJECT TITLE : ESVSSE Enabling Efficient, Secure, Verifiable Searchable Symmetric Encryption ABSTRACT: It is believed that symmetric searchable encryption, also known as SSE, will solve the problem of privacy in data outsourcing
PROJECT TITLE : ESA-Stream: Efficient Self-Adaptive Online Data Stream Clustering ABSTRACT: A wide variety of big data applications generate an enormous amount of streaming data that is high-dimensional, real-time, and constantly
PROJECT TITLE : Efficient Shapelet Discovery for Time Series Classification ABSTRACT: Recently, it was discovered that time-series shapelets, which are discriminative subsequences, are effective for the classification of time
PROJECT TITLE : Efficient Identity-based Provable Multi-Copy Data Possession in Multi-Cloud Storage ABSTRACT: A significant number of clients currently store multiple copies of their data on a variety of cloud servers. This helps

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry