AIMC Topic: Machine Learning

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Automated Anomaly Detection via Curiosity-Guided Search and Self-Imitation Learning.

IEEE transactions on neural networks and learning systems
Anomaly detection is an important data mining task with numerous applications, such as intrusion detection, credit card fraud detection, and video surveillance. However, given a specific complicated task with complicated data, the process of building...

Machine learning for understanding and predicting neurodevelopmental outcomes in premature infants: a systematic review.

Pediatric research
BACKGROUND: Machine learning has been attracting increasing attention for use in healthcare applications, including neonatal medicine. One application for this tool is in understanding and predicting neurodevelopmental outcomes in preterm infants. In...

Accuracy and Efficiency of Machine Learning-Assisted Risk-of-Bias Assessments in "Real-World" Systematic Reviews : A Noninferiority Randomized Controlled Trial.

Annals of internal medicine
BACKGROUND: Automation is a proposed solution for the increasing difficulty of maintaining up-to-date, high-quality health evidence. Evidence assessing the effectiveness of semiautomated data synthesis, such as risk-of-bias (RoB) assessments, is lack...

Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast.

Journal of chemical information and modeling
Deep learning has been a prevalence in computational chemistry and widely implemented in molecular property predictions. Recently, self-supervised learning (SSL), especially contrastive learning (CL), has gathered growing attention for the potential ...

Multi-Swarm Algorithm for Extreme Learning Machine Optimization.

Sensors (Basel, Switzerland)
There are many machine learning approaches available and commonly used today, however, the extreme learning machine is appraised as one of the fastest and, additionally, relatively efficient models. Its main benefit is that it is very fast, which mak...

AutoML-ID: automated machine learning model for intrusion detection using wireless sensor network.

Scientific reports
Momentous increase in the popularity of explainable machine learning models coupled with the dramatic increase in the use of synthetic data facilitates us to develop a cost-efficient machine learning model for fast intrusion detection and prevention ...

Correlation-Based Anomaly Detection Method for Multi-sensor System.

Computational intelligence and neuroscience
In industry, sensor-based monitoring of equipment or environment has become a necessity. Instead of using a single sensor, multi-sensor system is used to fully detect abnormalities in complex scenarios. Recently, physical models, signal processing te...

Big Transfer Learning for Fine Art Classification.

Computational intelligence and neuroscience
Automatic classification and retrieval of fine art collections have received much attention in recent years. In this article, we explore the applicability of convolutional neural networks (CNNs) for art-related image classification tasks. To examine ...

Short Sequence Chinese-English Machine Translation Based on Generative Adversarial Networks of Emotion.

Computational intelligence and neuroscience
With the steady growth of the global economy, the communication between countries in the world has become increasingly close. Due to its translation efficiency and other problems, the traditional manual translation has gradually failed to meet the cu...

Can machine learning methods accurately predict the molar absorption coefficient of different classes of dyes?

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this article, we provide a convenient tool for all researchers to predict the value of the molar absorption coefficient for a wide number of dyes without any computer costs. The new model is based on RFR method (ALogPS, OEstate + Fragmentor + QNPR...