AIMC Topic: Classification

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Fast convergence rates of deep neural networks for classification.

Neural networks : the official journal of the International Neural Network Society Feb 23, 2021
We derive the fast convergence rates of a deep neural network (DNN) classifier with the rectified linear unit (ReLU) activation function learned using the hinge loss. We consider three cases for a true model: (1) a smooth decision boundary, (2) smoot...
Machine Learning Probability Classification Entropy
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Classification aware neural topic model for COVID-19 disinformation categorisation.

PloS one Feb 18, 2021
The explosion of disinformation accompanying the COVID-19 pandemic has overloaded fact-checkers and media worldwide, and brought a new major challenge to government responses worldwide. Not only is disinformation creating confusion about medical scie...
Neural Networks, Computer COVID-19 Communication Classification Data Curation
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Generalized Learning Riemannian Space Quantization: A Case Study on Riemannian Manifold of SPD Matrices.

IEEE transactions on neural networks and learning systems Jan 4, 2021
Learning vector quantization (LVQ) is a simple and efficient classification method, enjoying great popularity. However, in many classification scenarios, such as electroencephalogram (EEG) classification, the input features are represented by symmetr...
Humans Neural Networks, Computer Machine Learning Algorithms Imagination Cues Reproducibility of Results Classification Image Processing, Computer-Assisted Movement Electroencephalography
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Continual Multiview Task Learning via Deep Matrix Factorization.

IEEE transactions on neural networks and learning systems Jan 4, 2021
The state-of-the-art multitask multiview (MTMV) learning tackles a scenario where multiple tasks are related to each other via multiple shared feature views. However, in many real-world scenarios where a sequence of the multiview task comes, the high...
Classification Regression Analysis Data Interpretation, Statistical Humans Schools Neural Networks, Computer Machine Learning Algorithms Models, Theoretical
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Gradients Cannot Be Tamed: Behind the Impossible Paradox of Blocking Targeted Adversarial Attacks.

IEEE transactions on neural networks and learning systems Jan 4, 2021
Despite their accuracy, neural network-based classifiers are still prone to manipulation through adversarial perturbations. These perturbations are designed to be misclassified by the neural network while being perceptually identical to some valid in...
Neural Networks, Computer Algorithms Reproducibility of Results Pattern Recognition, Automated Classification
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pcPromoter-CNN: A CNN-Based Prediction and Classification of Promoters.

Genes Dec 21, 2020
A promoter is a small region within the DNA structure that has an important role in initiating transcription of a specific gene in the genome. Different types of promoters are recognized by their different functions. Due to the importance of promoter...
Escherichia coli K12 Datasets as Topic Classification Promoter Regions, Genetic Neural Networks, Computer DNA, Bacterial Models, Genetic Genes, Bacterial
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Circular Complex-Valued GMDH-Type Neural Network for Real-Valued Classification Problems.

IEEE transactions on neural networks and learning systems Nov 30, 2020
Recently, applications of complex-valued neural networks (CVNNs) to real-valued classification problems have attracted significant attention. However, most existing CVNNs are black-box models with poor explanation performance. This study extends the ...
Benchmarking Classification Animals Models, Theoretical Humans Data Interpretation, Statistical Machine Learning Neural Networks, Computer Algorithms Databases, Factual
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Transforming the study of organisms: Phenomic data models and knowledge bases.

PLoS computational biology Nov 24, 2020
The rapidly decreasing cost of gene sequencing has resulted in a deluge of genomic data from across the tree of life; however, outside a few model organism databases, genomic data are limited in their scientific impact because they are not accompanie...
Humans Phenotype Animals Knowledge Bases Semantics Databases, Genetic Ecosystem Classification Models, Statistical Computational Biology Gene-Environment Interaction Models, Biological Models, Genetic Phenomics
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Scalable classification of organisms into a taxonomy using hierarchical supervised learners.

Journal of bioinformatics and computational biology Oct 29, 2020
Accurately identifying organisms based on their partially available genetic material is an important task to explore the phylogenetic diversity in an environment. Specific fragments in the DNA sequence of a living organism have been defined as DNA ba...
Chiroptera Rodentia Ferns Fungi DNA Barcoding, Taxonomic Classification Algorithms Deep Learning Animals Support Vector Machine Birds Databases, Genetic Phylogeny
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Country-level pandemic risk and preparedness classification based on COVID-19 data: A machine learning approach.

PloS one Oct 28, 2020
In this work we present a three-stage Machine Learning strategy to country-level risk classification based on countries that are reporting COVID-19 information. A K% binning discretisation (K = 25) is used to create four risk groups of countries base...
Reagent Kits, Diagnostic SARS-CoV-2 Models, Theoretical COVID-19 Humans Disaster Planning Global Health Support Vector Machine Machine Learning Algorithms Risk Assessment International Cooperation Decision Trees Pandemics Forecasting Clinical Laboratory Techniques Coronavirus Infections COVID-19 Testing Betacoronavirus Classification Pneumonia, Viral
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