AIMC Topic: Machine Learning

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Conservation machine learning: a case study of random forests.

Scientific reports
Conservation machine learning conserves models across runs, users, and experiments-and puts them to good use. We have previously shown the merit of this idea through a small-scale preliminary experiment, involving a single dataset source, 10 datasets...

RNA secondary structure prediction using deep learning with thermodynamic integration.

Nature communications
Accurate predictions of RNA secondary structures can help uncover the roles of functional non-coding RNAs. Although machine learning-based models have achieved high performance in terms of prediction accuracy, overfitting is a common risk for such hi...

Transfer Extreme Learning Machine with Output Weight Alignment.

Computational intelligence and neuroscience
Extreme Learning Machine (ELM) as a fast and efficient neural network model in pattern recognition and machine learning will decline when the labeled training sample is insufficient. Transfer learning helps the target task to learn a reliable model b...

Application of machine learning to the identification of joint degrees of freedom involved in abnormal movement during upper limb prosthesis use.

PloS one
To evaluate movement quality of upper limb (UL) prosthesis users, performance-based outcome measures have been developed that examine the normalcy of movement as compared to a person with a sound, intact hand. However, the broad definition of "normal...

Using machine learning to investigate the relationship between domains of functioning and functional mobility in older adults.

PloS one
Previous studies have shown that functional mobility, along with other physical functions, decreases with advanced age. However, it is still unclear which domains of functioning (body structures, body functions, and activities) are most closely relat...

Multifidelity computing for coupling full and reduced order models.

PloS one
Hybrid physics-machine learning models are increasingly being used in simulations of transport processes. Many complex multiphysics systems relevant to scientific and engineering applications include multiple spatiotemporal scales and comprise a mult...

Neural Networks with Emotion Associations, Topic Modeling and Supervised Term Weighting for Sentiment Analysis.

International journal of neural systems
Automated sentiment analysis is becoming increasingly recognized due to the growing importance of social media and -commerce platform review websites. Deep neural networks outperform traditional lexicon-based and machine learning methods by effective...

Towards effective deep transfer via attentive feature alignment.

Neural networks : the official journal of the International Neural Network Society
Training a deep convolutional network from scratch requires a large amount of labeled data, which however may not be available for many practical tasks. To alleviate the data burden, a practical approach is to adapt a pre-trained model learned on the...

Feasibility of machine learning methods for predicting hospital emergency room visits for respiratory diseases.

Environmental science and pollution research international
The prediction of hospital emergency room visits (ERV) for respiratory diseases after the outbreak of PM is of great importance in terms of public health, medical resource allocation, and policy decision support. Recently, the machine learning method...