[PDF] Top 20 A semi-supervised machine learning framework for microRNA classification

... to semi-super- vised ML ...expression classification [28], cancer sample classification [29], and phenotype prediction ...of semi- supervised learning using an integrated feature ... See full document

... To directly handle the problem of discriminative learning when labeled data is scarce, (Ororbia II et al., 2015) proposed deep hybrid architectures that could effectively leverage small amounts of labeled and ... See full document

... labeled classification, the generalization ability of the hypothesis learned on the initial training data is often very ...by semi-supervised learning may snowball themselves, which often ... See full document

... in Machine Learning hitherto, have tackled this need by exploiting statistical methods that learn from ...as Supervised and Unsupervised Learning can handle problems such as ... See full document

... Dacheng Tao (F’15) is Professor of Computer Sci- ence with the Centre for Quantum Computation & Intelligent Systems, and the Faculty of Engineering and Information Technology in the University of Technology Sydney. ... See full document

... vector machine (SVM) was used to learn to classify between the targets and backgrounds and the sentences were ranked accord- ing to the score assigned by the SVM (which is a proxy for P (x 1 = 1 | x 2 ... See full document

... investigates semi-supervised learn- ing of Gaussian mixture models using an uni- fied objective function taking both labeled and unlabeled data into ...UCI Machine Learning ...in ... See full document

... Although the aforementioned methods aim to reduce the domain discrepancy, they do not explic- itly minimize the distance between distributions, and some of them highly rely on the selection of pivot features. In our ... See full document

... using machine translation to translate labelled corpus from the source language into the target language or translate unlabelled data from the target language into the source language and applying monolingual ... See full document

... employ machine trans- lation tools to translate documents from one lan- guage domain to the other one and then induce low dimensional latent representations as interlingual representations (Littman et ... See full document

... the semi- supervised machine learning ...user classification or protocol is used to identify which classifications they do ...included classification techniques of network ... See full document

... respect, machine learning architecture can provide a great support in classification of OBS network ...traffic. Machine learning (ML) has been used profusely in a variety of application ... See full document

... the classification is not affected by an unfavourable segmentation, but it also means that a large number of segments (from a couple of dozen to a few hundred per swimming path) are ...manual classification ... See full document

... greedy learning can be followed by, or combined with, other learning procedures that fine-tune all of the weights to enhance the generative or discriminative performance of the entire ...by learning ... See full document

... text classification with a large number of categories ...a framework to incorporate unlabeled data in the Error-Correcting Output Coding (ECOC) setup by decomposing Multiclass problems into multiple binary ... See full document

... neural machine transla- tion (NMT) has made remarkable progress recently, NMT systems only rely on par- allel corpora for parameter ...a semi- supervised approach for training NMT models on the ... See full document

... This chapter starts by explaining the parameters that were used to evaluate the proposed methods. Next, it reports the evaluation results of the developed methods on the two datasets that included recordings of 19 PD ... See full document

... The manufacturing processes perhaps controlled by data driven models where these models have been of benefitting advantage in decision making for optimization of complex manufacturing procedures. These representations ... See full document

... This paper is an extension of work originally presented in the 7th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), 2016. It presents the use of ... See full document

... Carol Romanowski was my first graduate professor, and taught the first course I took in machine learning and data mining. In a sense she was behind me “before the beginning” of my Ph.D. journey. Now as I ... See full document