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Coupling Effect of Exploration Rate and Learning Rate for Optimized Scaled Reinforcement Learning
Reinforcement learning (RL) is making paradigm transformations in artificial intelligence frameworks in the field of autonomous robotics. This...
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Facial Micro-expression Modelling-Based Student Learning Rate Evaluation Using VGG–CNN Transfer Learning Model
Micro-facial expressions hold the potential to identify emotional states of students during their participation in online learning tasks. Through...
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Kronecker-factored Approximate Curvature with adaptive learning rate for optimizing model-agnostic meta-learning
Model-agnostic meta-learning (MAML) highlights the ability to quickly adapt to new tasks with only a small amount of labeled training data among many...
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Control learning rate for autism facial detection via deep transfer learning
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that affects social interaction and communication. Early detection of ASD can...
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To raise or not to raise: the autonomous learning rate question
There is a parameter ubiquitous throughout the deep learning world: learning rate. There is likewise a ubiquitous question: what should that learning...
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An Adaptive Learning Rate Deep Learning Optimizer Using Long and Short-Term Gradients Based on G–L Fractional-Order Derivative
Deep learning model is a multi-layered network structure, and the network parameters that evaluate the final performance of the model must be trained...
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Deep-learning based sleep apnea detection using sleep sound, SpO2, and pulse rate
Sleep apnea, a common sleep disorder where breathing is repeatedly interrupted during sleep, poses significant health risks. Traditional diagnostic...
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GLR: Gradient-Based Learning Rate Scheduler
Training a neural network is a complex and time-consuming process because of many combinations of hyperparameters that have to be adjusted and...
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Heuristic Technique to Find Optimal Learning Rate of LSTM for Predicting Student Dropout Rate
Predictive analytics is being increasingly recognized as being important for evaluating university students’ academic achievement. Utilizing big data...
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An efficient multicast multi-rate reinforcement learning based opportunistic routing algorithm
Multicasting through device-to-device communication (MD2D) is a promising solution for handling the heavy load caused by the extraordinary high...
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AdaLip: An Adaptive Learning Rate Method per Layer for Stochastic Optimization
Various works have been published around the optimization of Neural Networks that emphasize the significance of the learning rate. In this study we...
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Griffiths’ Variable Learning Rate Online Sequential Learning Algorithm for Feed-Forward Neural Networks
AbstractFor online sequential training of deep neural networks, where the training data set is chaotic in nature, it becomes quite challenging for...
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Detection of non-periodic low-rate denial of service attacks in software defined networks using machine learning
In this paper, we propose a novel approach to detect non-periodic Low-rate Denial of Service attacks in Software Defined Networks using Machine...
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A novel framework using 3D-CNN and BiLSTM model with dynamic learning rate scheduler for visual speech recognition
Visual Speech Recognition (VSR) is an appealing technology for predicting and analyzing spoken language based on lip movements. Previous research in...
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Machine learning model for healthcare investments predicting the length of stay in a hospital & mortality rate
The demand for healthcare workers and infrastructure from an alarmingly growing patient population may contribute to the increased Length of Stay...
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Enhancing cure rate analysis through integration of machine learning models: a comparative study
Cure rate models have been thoroughly investigated across various domains, encompassing medicine, reliability, and finance. The merging of machine...
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P4httpGuard: detection and prevention of slow-rate DDoS attacks using machine learning techniques in P4 switch
Software Defined Networks (SDNs) offer a comprehensive network view by separating the control plane from the data plane. However, SDNs are vulnerable...
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An extended TLD tracking algorithm using co-training learning for low frame rate videos
The conventional tracking-learning-detection (TLD) algorithm is sensitive to illumination changes, clutter, significant changes of target shape...
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Rate Adaptation Aware Positioning for Flying Gateways Using Reinforcement Learning
With the growing connectivity demands, Unmanned Aerial Vehicles (UAVs) have emerged as a prominent component in the deployment of Next Generation...
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Localization Through Deep Learning in New and Low Sampling Rate Environments
Source localization in wireless networks is essential for spectrum utilization optimization. Traditional methods often require extensive transmitter...