Showing 1 - 16 results of 16 for search '(( complementary system algorithm ) OR ((( recent rd algorithm ) OR ( neural coding algorithm ))))', query time: 0.11s Refine Results
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    Application of Red Deer Algorithm in Optimizing Complex functions by Zitar, Raed

    Published 2021
    “…The Red Deer algorithm (RDA), a recently developed population-based meta-heuristic algorithm, is examined in this paper with the optimization task of complex functions. …”
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    Review and analysis for the Red Deer Algorithm by Zitar, Raed

    Published 2021
    “…The Red Deer algorithm (RDA), a recent population-based meta-heuristic algorithm, is thoroughly reviewed. …”
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    Advanced Quantum Control with Ensemble Reinforcement Learning: A Case Study on the XY Spin Chain by Farshad Rahimi Ghashghaei (20880995)

    Published 2025
    “…<p dir="ltr">This research presents an ensemble Reinforcement Learning (RL) approach that combines Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) algorithms to tackle quantum control problems. This research aims to use the complementary strengths of DQN and PPO algorithms to develop robust and adaptive control policies for noisy and uncertain quantum systems. …”
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    Ultra-small cell networks with collaborative RF and lightwave power transfer by Tran, HA-Vu

    Published 2019
    “…In the network, the optical transmitters play the primary role and are responsible for delivering information and power over the visible light while the RF AP acts as a complementary power transfer system. Thus, we propose a novel collaborative RF and lightwave resource allocation scheme for hybrid RF/VLC ultra-small cell networks. …”
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    Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

    Published 2024
    “…For tabular data, we also present the Auto-Inflater neural network, utilizing an exponential loss function for Autoencoders. …”
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    Developing an online hate classifier for multiple social media platforms by Joni Salminen (7434770)

    Published 2020
    “…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …”