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Membalas thread yuliuseka • 27-05-2024 08:30

Literature Review and Theories in Neuroevolutionary Learning Introduction

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Membalas thread yuliuseka • 27-05-2024 08:30

Literature Review and Theories in Surrogate Modeling Introduction

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Membalas thread yuliuseka • 27-05-2024 08:30

Literature Review and Theories in Elasticsearch Introduction

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Membalas thread yuliuseka • 27-05-2024 08:30

Literature Review and Theories in Unsupervised Feature Learning Introduction

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Membalas thread yuliuseka • 27-05-2024 08:30

Literature Review and Theories in Graph Neural Networks (GNNs) Introduction

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Membuat thread • 27-05-2024 08:26

Literature Review and Theories in Graph Neural Networks (GNNs) Introduction

Literature Review and Theories in Graph Neural Networks (GNNs) Introduction Graph Neural Networks (GNNs) are a class of neural networks designed to handle data structured as graphs. Unlike traditional neural networks that process fixed-size vector data, GNNs can operate on graph-structured data, wh

Membuat thread • 27-05-2024 08:24

Literature Review and Theories in Unsupervised Feature Learning Introduction

Literature Review and Theories in Unsupervised Feature Learning Introduction Unsupervised feature learning is a subset of machine learning where the goal is to discover and learn useful features from unlabeled data. Unlike supervised learning, which relies on labeled data for training, unsupervised

Membuat thread • 27-05-2024 08:22

Literature Review and Theories in Elasticsearch Introduction

Literature Review and Theories in Elasticsearch Introduction Elasticsearch is an open-source, distributed search and analytics engine built on top of Apache Lucene. It is designed for horizontal scalability, reliability, and real-time search capabilities. Elasticsearch is widely used for log and ev

Membuat thread • 27-05-2024 08:20

Literature Review and Theories in Surrogate Modeling Introduction

Literature Review and Theories in Surrogate Modeling Introduction Surrogate modeling, also known as metamodeling, is a technique used to approximate complex and computationally expensive simulations with simpler models. These surrogate models serve as substitutes for detailed simulations, providing

Membuat thread • 27-05-2024 08:18

Literature Review and Theories in Neuroevolutionary Learning Introduction

Literature Review and Theories in Neuroevolutionary Learning Introduction Neuroevolutionary learning combines principles from neural networks and evolutionary algorithms to create and optimize artificial neural network architectures and weights. This approach leverages the power of evolutionary com

Membuat thread • 27-05-2024 08:16

Literature Review and Theories in Adaptive Resonance Theory (ART) Introduction

Literature Review and Theories in Adaptive Resonance Theory (ART) Introduction Adaptive Resonance Theory (ART) is a cognitive and neural theory developed by Stephen Grossberg in the late 1970s to explain how the brain processes information in a stable yet adaptable manner. ART addresses the challen

Membuat thread • 27-05-2024 08:13

Literature Review and Theories in Neuromorphic Computing Introduction

Literature Review and Theories in Neuromorphic Computing Introduction Neuromorphic computing is a branch of artificial intelligence and computer engineering that aims to design computer systems inspired by the human brain's architecture and functionality. This field encompasses various interdiscipl

Membuat thread • 27-05-2024 08:12

Literature Review and Theories in Neuromorphic Computing Introduction

Literature Review and Theories in Neuromorphic Computing Introduction Neuromorphic computing is a branch of artificial intelligence and computer engineering that aims to design computer systems inspired by the human brain's architecture and functionality. This field encompasses various interdiscipl

Membuat thread • 25-05-2024 16:21

Literature Review on Capsule Networks

Literature Review on Capsule Networks Introduction Capsule Networks (CapsNets) represent a novel architecture in deep learning designed to address some limitations of traditional convolutional neural networks (CNNs). Proposed by Geoffrey Hinton and his colleagues, Capsule Networks aim to better c...

Membuat thread • 25-05-2024 16:19

Literature Review on Anomaly Detection

Literature Review on Anomaly Detection Introduction Anomaly detection is a critical area of machine learning and data analysis that involves identifying patterns in data that do not conform to expected behavior. These anomalies can indicate critical incidents, such as fraud, network intrusions, e...

Membuat thread • 25-05-2024 16:14

Literature Review on Few-shot Learning

Literature Review on Few-shot Learning Introduction Few-shot learning (FSL) is a subfield of machine learning that focuses on training models to recognize new classes with only a few labeled examples. This is in contrast to traditional machine learning methods, which typically require large amounts

Membuat thread • 25-05-2024 16:12

Literature Review on Quantum-inspired Computing

Literature Review on Quantum-inspired Computing Introduction Quantum-inspired computing leverages principles and algorithms inspired by quantum mechanics to solve complex computational problems. While distinct from quantum computing, which relies on actual quantum bits (qubits) and quantum gates,...

Membuat thread • 25-05-2024 16:10

Literature Review on Automated Machine Learning (AutoML)

Literature Review on Automated Machine Learning (AutoML) Introduction Automated Machine Learning (AutoML) represents a significant advancement in the field of machine learning by automating the end-to-end process of applying machine learning to real-world problems. AutoML aims to make machine lea...

Membuat thread • 25-05-2024 12:04

Literature Review and Theoretical Review of Multi-instance Learning

Literature Review and Theoretical Review of Multi-instance Learning Introduction Multi-instance learning (MIL) is a machine learning paradigm where each example is represented by a bag of instances instead of a single feature vector. This review provides an overview of the historical development,...

Membuat thread • 25-05-2024 12:02

Literature Review and Theoretical Review of Hyperparameter Optimization

Literature Review and Theoretical Review of Hyperparameter Optimization Introduction Hyperparameter optimization is a critical aspect of machine learning model development, focusing on finding the optimal configuration of hyperparameters to improve model performance. This review explores the hist...

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