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Unsupervised Machine Learning

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An unsupervised EEG decoding system for human emotion recognition.

Neural networks : the official journal of the International Neural Network Society
Emotion plays a vital role in human health and many aspects of life, including relationships, behaviors and decision-making. An intelligent emotion recognition system may provide a flexible method to monitor emotion changes in daily life and send war...

Exon level machine learning analyses elucidate novel candidate miRNA targets in an avian model of fetal alcohol spectrum disorder.

PLoS computational biology
Gestational alcohol exposure causes fetal alcohol spectrum disorder (FASD) and is a prominent cause of neurodevelopmental disability. Whole transcriptome sequencing (RNA-Seq) offer insights into mechanisms underlying FASD, but gene-level analysis pro...

DynMat, a network that can learn after learning.

Neural networks : the official journal of the International Neural Network Society
To survive in the dynamically-evolving world, we accumulate knowledge and improve our skills based on experience. In the process, gaining new knowledge does not disrupt our vigilance to external stimuli. In other words, our learning process is 'accum...

Unsupervised tumor detection in Dynamic PET/CT imaging of the prostate.

Medical image analysis
Early detection and localization of prostate tumors pose a challenge to the medical community. Several imaging techniques, including PET, have shown some success. But no robust and accurate solution has yet been reached. This work aims to detect pros...

An unsupervised neuromorphic clustering algorithm.

Biological cybernetics
Brains perform complex tasks using a fraction of the power that would be required to do the same on a conventional computer. New neuromorphic hardware systems are now becoming widely available that are intended to emulate the more power efficient, hi...

Seq2seq Fingerprint with Byte-Pair Encoding for Predicting Changes in Protein Stability upon Single Point Mutation.

IEEE/ACM transactions on computational biology and bioinformatics
The engineering of stable proteins is crucial for various industrial purposes. Several machine learning methods have been developed to predict changes in the stability of proteins corresponding to single point mutations. To improve the prediction acc...

Vision-Based Robot Navigation through Combining Unsupervised Learning and Hierarchical Reinforcement Learning.

Sensors (Basel, Switzerland)
Extensive studies have shown that many animals' capability of forming spatial representations for self-localization, path planning, and navigation relies on the functionalities of place and head-direction (HD) cells in the hippocampus. Although there...

Analysis of a CT patient dose database with an unsupervised clustering approach.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: This study investigated the benefits of implementing a cluster analysis technique to extract relevant information from a computed tomography (CT) dose registry archive.

Flexible unsupervised feature extraction for image classification.

Neural networks : the official journal of the International Neural Network Society
Dimensionality reduction is one of the fundamental and important topics in the fields of pattern recognition and machine learning. However, most existing dimensionality reduction methods aim to seek a projection matrix W such that the projection Wx i...

Unsupervised abnormality detection through mixed structure regularization (MSR) in deep sparse autoencoders.

Medical physics
PURPOSE: The purpose of this study is to introduce and evaluate the mixed structure regularization (MSR) approach for a deep sparse autoencoder aimed at unsupervised abnormality detection in medical images. Unsupervised abnormality detection based on...