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Machine Learning at the Edge

In this chapter we start by introducing machine learning (ML). We explain the terminology such as supervised and unsupervised ML. We explain the ML tasks called classification and regression. Then we intro...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2019
  • C
  • Link
Result

Hitoshi Iba: Evolutionary approach to machine learning and deep neural networks: neuro-evolution and gene regulatory networks (review)

The book’s title promises an evolutionary approach to machine learning and deep neural networks. In fact, it covers both an evolutionary approach to machine learning and machine learning approach ...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2019
  • O
Result

Using Machine Learning Methods in Environmental Risk Assessment -- Overview

In the past few years the evolution of Machine Learning (ML) techniques was significant. The number of fields, where ML is employed, is still continuously growing problems from the field (ERA) is ''machine...

IN - Informatika

  • 2006
  • D
Result

ML-DEECo: a Machine-Learning-Enabled Framework for Self-organizing Components (software)

A software artifact for the paper "ML-DEECo: a Machine-Learning-Enabled Framework for Self-organizing Components" by Michal Töpfer, Milad Abdullah, Martin Kruliš, Tomáš Bureš, and Petr Hnětynka (DOI of the paper 1...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2022
  • R
  • Link
Result

Application of Machine Learning Methods in NPH

The chapter explores the use of machine learning (ML) in Normal Pressure Hydrocephalus (NPH) diagnosis and treatment. It delves into various ML techniques in predictive medicine. The chapter also discusses differen...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2023
  • O
  • Link
Result

Online ML Self-adaptation in Face of Traps

Online machine learning (ML) is often used in selfadaptive systems, applying online ML for self-adaptation can be challenging, and not many papers report its limitations. Recently, we experimented with applying onl...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2023
  • D
  • Link
Result

Authorship Attribution: Comparison of Single-layer and Double-layer Machine Learning

documents, but currently prevailing techniques build upon the machine learning (ML) approach. In this paper, two machine learning approaches are compared: Single-layer ML for the machine...

AI - Jazykověda

  • 2012
  • D
  • Link
Result

Cross ML for Io(H)T Network Traffic Classification: A New Approach Towards Standardization

healthcare. This study delves into Cross-Machine Learning (Cross-ML), a novel approach to leveraging data from multiple sources to enhance Machine Learning (ML)-based Network......

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2024
  • D
  • Link
Result

Machine learning in finance and accounting

. It applies Machine learning (ML) to enhance longevity risk management by life insurance companies and pension fund managers. The book shows how ML can help improve mortality forecasting. It introduces kernel swit...

Finance

  • 2021
  • C
  • Link
Result

Artificial Neural Networks and Machine Learning – ICANN 2018. Proceedings, Part II

, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bi...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2018
  • O
  • Link
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