A Maximal Correlation Approach to Imposing Fairness in Machine Learning[阅读笔记] 实名用户 数学、统计学在读。兴趣方向社会学,心理学8 人赞同了该文章 这篇文章来自于MIT EECS Dept的文章,发表在Entropy上[1]。 A Maximal Correlation Framework for Fair Machine Learningwww.mdpi.com/1099-4300/24/4/...
MACHINE learningERROR functionsANALYTICAL solutionsCLASSIFICATION algorithmsGENERALIZATIONExtreme learning machine (ELM) has shown to be a suitable algorithm for classification problems. Several ensemble meta-algorithms have been developed in order to generalize the results of ELM models....
Machine Learning Detection of Correlations in Snapshots of Ultracold Atoms in Optical LatticesRecent proposals have suggested the use of supervised learning ... S Striegel,E Ibarra-García-Padilla,E Khatami 被引量: 0发表: 2023年 Machine learning‐assisted study of correlation between post‐transition...
In medicinal chemistry and drug design, machine learning (ML) has long been applied to predict molecular properties of compounds, especially biological activity1,2. ML models can be developed to qualitatively or quantitatively predict compound activity against given biological targets. For early compound...
Although the possible range of the considered feature candidates has expanded, it might be inappropriate to directly involve them in neural network or any other machine learning algorithms. In response, a data preprocessing, namely feature scaling, is opted for normalizing the feature candidates. The...
Machine learning is widely applied in drug discovery research to predict molecular properties and aid in the identification of active compounds. Herein, we introduce a new approach that uses model-internal information from compound activity predictions to uncover relationships between target proteins. On ...
Such domain shifts, common in practical scenarios, severely damage the performance of conventional machine learning methods. Supervised domain adaptation methods have been proposed for the case when the target data have labels, including some that perform very well despite being frustratingly easy to ...
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application. ...
Felsberg, “Beyond correlation filters: Learning continuous convolution operators for visual tracking,” in ECCV, 2016. 很强悍的算法,由大神Danelljan提出,可看作世宗雍正,算法简称C-COT。 M. Danelljan, G. Bhat, F. Shahbaz Khan, and M. Felsberg, “Eco: Efficient convolution operators for tracking,...
Recently, a novel approach that combines CNA with machine learning (ML) techniques, was used to predict the presence of metabolic pathways in tomato correlation networks (CN)29. Here, we investigated the response of two Brachypodium sylvaticum accessions (Osl1 and Ain1) to cold and freezing ...