Terahertz channel propagation phenomena, measurement techniques and modeling for 6G wireless communication applications: A survey, open challenges and …
The Terahertz (THz) band (0.3-3.0 THz), spans a great portion of the Radio Frequency (RF)
spectrum that is mostly unoccupied and unregulated. It is a potential candidate for …
spectrum that is mostly unoccupied and unregulated. It is a potential candidate for …
[图书][B] Clustering
R Xu, D Wunsch - 2008 - books.google.com
This is the first book to take a truly comprehensive look at clustering. It begins with an
introduction to cluster analysis and goes on to explore: proximity measures; hierarchical …
introduction to cluster analysis and goes on to explore: proximity measures; hierarchical …
A survey of kernel and spectral methods for clustering
Clustering algorithms are a useful tool to explore data structures and have been employed
in many disciplines. The focus of this paper is the partitioning clustering problem with a …
in many disciplines. The focus of this paper is the partitioning clustering problem with a …
Data-driven robust optimization based on kernel learning
We propose piecewise linear kernel-based support vector clustering (SVC) as a new
approach tailored to data-driven robust optimization. By solving a quadratic program, the …
approach tailored to data-driven robust optimization. By solving a quadratic program, the …
Scaling, power, and the future of CMOS
This paper briefly reviews the forces that caused the power problem, the solutions that were
applied, and what the solutions tell us about the problem. As systems became more power …
applied, and what the solutions tell us about the problem. As systems became more power …
A comprehensive review on the variants of support vector machines
Machine learning (ML) represents the automated extraction of models (or patterns) from
data. All ML techniques start with data. These data describe the desired relationship …
data. All ML techniques start with data. These data describe the desired relationship …
Document clustering method using dimension reduction and support vector clustering to overcome sparseness
S Jun, SS Park, DS Jang - Expert Systems with Applications, 2014 - Elsevier
Many studies on developing technologies have been published as articles, papers, or
patents. We use and analyze these documents to find scientific and technological trends. In …
patents. We use and analyze these documents to find scientific and technological trends. In …
Support vector clustering of electrical load pattern data
G Chicco, IS Ilie - IEEE Transactions on Power Systems, 2009 - ieeexplore.ieee.org
This paper presents an original and effective application of support vector clustering (SVC)
to electrical load pattern classification. The proposed SVC-based approach combines the …
to electrical load pattern classification. The proposed SVC-based approach combines the …
A support vector approach to censored targets
PK Shivaswamy, W Chu… - … conference on data …, 2007 - ieeexplore.ieee.org
Censored targets, such as the time to events in survival analysis, can generally be
represented by intervals on the real line. In this paper, we propose a novel support vector …
represented by intervals on the real line. In this paper, we propose a novel support vector …
Parametric models and non-parametric machine learning models for predicting option prices: Empirical comparison study over KOSPI 200 Index options
We investigated the performance of parametric and non-parametric methods concerning the
in-sample pricing and out-of-sample prediction performances of index options. Comparisons …
in-sample pricing and out-of-sample prediction performances of index options. Comparisons …