AIMC Topic: Machine Learning

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Representation learning for continuous action spaces is beneficial for efficient policy learning.

Neural networks : the official journal of the International Neural Network Society
Deep reinforcement learning (DRL) breaks through the bottlenecks of traditional reinforcement learning (RL) with the help of the perception capability of deep learning and has been widely applied in real-world problems. While model-free RL, as a clas...

Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives.

Sensors (Basel, Switzerland)
This paper presents the findings of detailed and comprehensive technical literature aimed at identifying the current and future research challenges of tactical autonomy. It discusses in great detail the current state-of-the-art powerful artificial in...

Detection of factors affecting kidney function using machine learning methods.

Scientific reports
Due to the increasing prevalence of chronic kidney disease and its high mortality rate, study of risk factors affecting the progression of the disease is of great importance. Here in this work, we aim to develop a framework for using machine learning...

A robust and resilience machine learning for forecasting agri-food production.

Scientific reports
This research proposes a new framework for agri-food capacity production by considering resiliency and robustness and paying attention to disruption and risk for the first time. It is applied robust stochastic optimization by adding robustness to the...

Machine learning computational tools to assist the performance of systematic reviews: A mapping review.

BMC medical research methodology
BACKGROUND: Within evidence-based practice (EBP), systematic reviews (SR) are considered the highest level of evidence in that they summarize the best available research and describe the progress in a determined field. Due its methodology, SR require...

Improving Inertial Sensor-Based Activity Recognition in Neurological Populations.

Sensors (Basel, Switzerland)
Inertial sensor-based human activity recognition (HAR) has a range of healthcare applications as it can indicate the overall health status or functional capabilities of people with impaired mobility. Typically, artificial intelligence models achieve ...

Application for Recognizing Sign Language Gestures Based on an Artificial Neural Network.

Sensors (Basel, Switzerland)
This paper presents the development and implementation of an application that recognizes American Sign Language signs with the use of deep learning algorithms based on convolutional neural network architectures. The project implementation includes th...

Application of Machine Learning to Child Mode Choice with a Novel Technique to Optimize Hyperparameters.

International journal of environmental research and public health
Travel mode choice (TMC) prediction is crucial for transportation planning. Most previous studies have focused on TMC in adults, whereas predicting TMC in children has received less attention. On the other hand, previous children's TMC prediction stu...

Accuracy and data efficiency in deep learning models of protein expression.

Nature communications
Synthetic biology often involves engineering microbial strains to express high-value proteins. Thanks to progress in rapid DNA synthesis and sequencing, deep learning has emerged as a promising approach to build sequence-to-expression models for stra...