Abstract: This paper presents a novel optimized kernel k-means algorithm (OKKC) to combine multiple data sources for clustering analysis. The algorithm uses an alternating minimization framework to ...
The area of approximation algorithms is aimed at giving provable guarantees on the performance of heuristics for hard problems. The course will present general techniques (such as convex ...
Abstract: Hyperspectral images possess the characteristics of high dimensionality, which causes “dimensional disaster” and low classification accuracy. In order to solve the problems, based on ...
A memristor is a non-linear element. The chaotic system constructed by it can improve its unpredictability and complexity. Parameter identification of a memristive chaotic system is the primary task ...
Sirona Medical, a company developing an “operating system” for digital radiology, has acquired Nines — a company that has developed FDA-cleared analysis and triage algorithms. This acquisition comes ...
Machine Learning Commons for OpenSearch is a new solution that make it easy to develop new machine learning feature. It allows engineers to leverage existing opensource machine learning algorithms and ...
knncolle is a header-only C++ library that collects a variety of different k-nearest neighbor algorithms under a consistent interface. The aim is to enable downstream libraries to easily switch ...
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