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 …
Efficient differentially private kernel support vector classifier for multi-class classification
In this paper, we propose a multi-class classification method using kernel supports and a
dynamical system under differential privacy. For small datasets, kernel methods, such as …
dynamical system under differential privacy. For small datasets, kernel methods, such as …
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 …
Soft clustering using weighted one-class support vector machines
M Bicego, MAT Figueiredo - Pattern Recognition, 2009 - Elsevier
This paper describes a new soft clustering algorithm in which each cluster is modelled by a
one-class support vector machine (OC-SVM). The proposed algorithm extends a previously …
one-class support vector machine (OC-SVM). The proposed algorithm extends a previously …
SVStream: A support vector-based algorithm for clustering data streams
In this paper, we propose a novel data stream clustering algorithm, termed SVStream, which
is based on support vector domain description and support vector clustering. In the …
is based on support vector domain description and support vector clustering. In the …
Machine learning for automated quality assurance in radiotherapy: A proof of principle using EPID data description
Purpose Developing automated methods to identify task‐driven quality assurance (QA)
procedures is key toward increasing safety, efficacy, and efficiency. We investigate the use …
procedures is key toward increasing safety, efficacy, and efficiency. We investigate the use …
Improving memory-based collaborative filtering via similarity updating and prediction modulation
Memory-based collaborative filtering (CF) makes recommendations based on a collection of
user preferences for items. The idea underlying this approach is that the interests of an …
user preferences for items. The idea underlying this approach is that the interests of an …
Sentiment visualization and classification via semi-supervised nonlinear dimensionality reduction
Sentiment analysis, which detects the subjectivity or polarity of documents, is one of the
fundamental tasks in text data analytics. Recently, the number of documents available online …
fundamental tasks in text data analytics. Recently, the number of documents available online …
Driving style analysis by classifying real-world data with support vector clustering
Y Feng, S Pickering, E Chappell… - 2018 3rd IEEE …, 2018 - ieeexplore.ieee.org
All drivers have their own habitual choice of driving behavior, causing variations in fuel
consumption. It would be beneficial to classify these driving styles and extract the most …
consumption. It would be beneficial to classify these driving styles and extract the most …
Automatic brain tumor segmentation in multispectral MRI volumes using a fuzzy c-means cascade algorithm
The aim of this study was to establish a multi-stage fuzzy c-means (FCM) framework for the
automatic and accurate detection of brain tumors from multimodal 3D magnetic resonance …
automatic and accurate detection of brain tumors from multimodal 3D magnetic resonance …