Journal ArticleDOI
A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms, Experimental Analysis, Prospects and Challenges
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TLDR
All the algorithms studied in this paper will be evaluated with exhaustive testing in order to analyze their capabilities in standard classification problems, particularly considering dimensionality reduction and kernelization.About:
This article is published in Neurocomputing.The article was published on 2021-02-15. It has received 71 citations till now. The article focuses on the topics: Metric (mathematics) & Dimensionality reduction.read more
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Real and Complex Analysis. By W. Rudin. Pp. 412. 84s. 1966. (McGraw-Hill, New York.)
TL;DR: In this paper, the Riesz representation theorem is used to describe the regularity properties of Borel measures and their relation to the Radon-Nikodym theorem of continuous functions.
Journal ArticleDOI
Audio self-supervised learning: A survey
Shuo Liu,Adria Mallol-Ragolta,Emilia Parada-Cabeleiro,Kun Qian,Xingshuo Jing,Alexander Kathan,Bin Hu,Björn Schuller +7 more
TL;DR: Huitt et al. as discussed by the authors presented an overview of the self-supervised learning (SSL) techniques used in audio and speech processing applications, and summarized the empirical works that exploit audio modality in multi-modal SSL frameworks and the existing suitable benchmarks to evaluate the power of SSL in the computer audition domain.
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A Unified Hierarchical XGBoost model for classifying priorities for COVID-19 vaccination campaign
TL;DR: In this article , a machine learning algorithm, namely hierarchical priority classification eXtreme gradient boosting, is proposed for priority classification for COVID-19 vaccine administration using the Italian Federation of General Practitioners dataset that contains Electronic Health Record data of 17k patients.
Journal ArticleDOI
A Unified Hierarchical XGBoost Model for Classifying Priorities for COVID-19 Vaccination Campaign.
TL;DR: In this paper, a machine learning algorithm, namely hierarchical priority classification eXtreme gradient boosting, is proposed for priority classification for COVID-19 vaccine administration using the Italian Federation of General Practitioners dataset that contains Electronic Health Record data of 17k patients.
Journal ArticleDOI
Scale-adaptive super-feature based MetricUNet for brain tumor segmentation
TL;DR: Wang et al. as discussed by the authors proposed a scale-adaptive super-feature based method for brain tumor segmentation, which can reduce the computation to about 1/11 of the original MetricUNet and focus more attention on the edge regions.
References
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Book
Convex Optimization
Stephen Boyd,Lieven Vandenberghe +1 more
TL;DR: In this article, the focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them, and a comprehensive introduction to the subject is given. But the focus of this book is not on the optimization problem itself, but on the problem of finding the appropriate technique to solve it.
Some methods for classification and analysis of multivariate observations
TL;DR: The k-means algorithm as mentioned in this paper partitions an N-dimensional population into k sets on the basis of a sample, which is a generalization of the ordinary sample mean, and it is shown to give partitions which are reasonably efficient in the sense of within-class variance.
Book
Matrix Analysis
Roger A. Horn,Charles R. Johnson +1 more
TL;DR: In this article, the authors present results of both classic and recent matrix analyses using canonical forms as a unifying theme, and demonstrate their importance in a variety of applications, such as linear algebra and matrix theory.
Journal ArticleDOI
A Tutorial on Support Vector Machines for Pattern Recognition
TL;DR: There are several arguments which support the observed high accuracy of SVMs, which are reviewed and numerous examples and proofs of most of the key theorems are given.