14 papers · ranked by Valyu relevance
Andreas Holzinger
Machine learning (ML) is the fastest growing field in computer science, and health informatics is among the greatest challenges. The goal of ML is to develop algorithms which can learn and improve over time and can be used for predictions. Most ML researchers concentrate on automatic machine learning (aML), where great…
Thomas Bohnstingl, Franz Scherr, Christian Pehle, Karlheinz Meier + 1 more
'Wolfgang Maass'] Hyperparameters and learning algorithms for neuromorphic hardware are usually chosen by hand to suit a particular task. In contrast, networks of neurons in the brain were optimized through extensive evolutionary and developmental processes to work well on a range of computing and learning tasks.…
Senerath Mudalige Don Alexis Chinthaka Jayatilake, Gamage Upeksha Ganegoda
In the present day, there are many diseases which need to be identified at their early stages to start relevant treatments. If not, they could be uncurable and deadly. Due to this reason, there is a need of analysing complex medical data, medical reports, and medical images at a lesser time but with greater accuracy.…
Mert Bal, M. Fatih Amasyali, Hayri Sever, Guven Kose + 1 more
The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select…
Steven A. Frank, Antonio M. Scarfone
Diverse learning algorithms, optimization methods, and natural selection share a common mathematical structure despite their apparent differences. Here, I show that a simple notational partitioning of change by the Price equation reveals a universal force-metric-bias (FMB) law: $Δθ=(Mf+b+ξ)$. The force $f$ drives…
Angeliki Pantazi, Bipin Rajendran, Osvaldo Simeone, Emre Neftci
The brain is equipped with impressive learning capabilities, enabling animals to dynamically adapt to the surrounding world. Hebbian learning and Spike-Timing Dependent Plasticity (STDP) are commonly employed learning rules in neuro-inspired models. The convergence properties and computational characteristics remain…
Paola Patricia Ariza-Colpas, Enrico Vicario, Ana Isabel Oviedo-Carrascal, Shariq Butt Aziz + 7 more
The Assisted Living Environments Research Area-AAL (Ambient Assisted Living), focuses on generating innovative technology, products, and services to assist, medical care and rehabilitation to older adults, to increase the time in which these people can live. independently, whether they suffer from neurodegenerative…
Hiromichi Tsukada, Minoru Tsukada
The spatiotemporal learning rule (STLR) proposed based on hippocampal neurophysiological experiments is essentially different from the Hebbian learning rule (HEBLR) in terms of the self-organization mechanism. The difference is the self-organization of information from the external world by firing (HEBLR) or not firing…
Hanzhong Zhang, Jibin Yin, Haoyang Wang, Michael E. Hahn
Based on Maslow’s hierarchy of needs theory, we have proposed a novel machine learning algorithm that combines factors of the environment and its own needs to make decisions for different states of an agent. This means it can be applied to the gait generation of a quadruped robot, which needs to make demand decisions.…
Arushi Agarwal, Purushottam Sharma, Mohammed Alshehri, Ahmed A. Mohamed + 2 more
'Ahmed A. Mohamed' 'Osama Alfarraj' 'Mamoun Alazab'] In today’s cyber world, the demand for the internet is increasing day by day, increasing the concern of network security. The aim of an Intrusion Detection System (IDS) is to provide approaches against many fast-growing network attacks (e.g., DDoS attack, Ransomware…
Boštjan Brumen, Aleš Černezel, Leon Bošnjak, Gholamreza Anbarjafari
Much research has been conducted in the area of machine learning algorithms; however, the question of a general description of an artificial learner’s (empirical) performance has mainly remained unanswered. A general, restrictions-free theory on its performance has not been developed yet. In this study, we investigate…
Geoffrey E Hinton
What is machine learning? Machine learning is a type of statistics that places particular emphasis on the use of advanced computational algorithms. As computers become more powerful, and modern experimental methods in areas such as imaging generate vast bodies of data, machine learning is becoming ever more important…
Jayashree Rajesh Prasad, Shashikant V. Athawale, Roshani Raut, Sonali Patil + 2 more
The current work describes a blockchain-based optimization approach that mimics the psychological mental illness evaluation procedure and evaluates mental fitness. Combining lightweight models with blockchains can give a variety of benefits in the healthcare business. This study aims to offer an improved review and…
Robert Legenstein, Niko Wilbert, Laurenz Wiskott, Abigail Morrison
Humans and animals are able to learn complex behaviors based on a massive stream of sensory information from different modalities. Early animal studies have identified learning mechanisms that are based on reward and punishment such that animals tend to avoid actions that lead to punishment whereas rewarded actions are…