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Low-resource neural machine translation for Southern African languages
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Mixed-Criticality Scheduling Using Reinforcement Learning
Published 2023“…With plenty of researchers approaching the schedulability of such systems with various objectives, our aim in this study is to shed light on the promising nature of emergent machine learning technologies, specifically Reinforcement Learning. …”
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A learning framework for zero-knowledge game playing agents
Published 2013Get full text
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Unsupervised feature learning for speech using correspondence and Siamese networks
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Deep Reinforcement Learning-Based Approaches for the MPPT Control of Standalone Solar PV Systems
Published 2025“…Reinforcement learning (RL) is a model-free optimization approach that can learn solar PV behaviour and store and reuse optimization information for future optimization tasks. …”
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Nonlinear adaptation of established linear and predictive control laws through safe reinforcement learning
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A framework for sustainable slum development based on zero waste concept: "Learn to Earn Model"
Published 2019“…Teaching them new skills through the "Learn to Earn Model'', will help them generate income which turns the slum into a catalyst for the economy rather than a burden on it. …”
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Secondary school teachers’ experiences of a zero-tolerance approach to learner discipline
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Acoustic unit discovery with zero-resource applications
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Maximising exploration and discovery in unknown large intricate 3D worlds
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Identifying water wastage in deep-level mines using novel simulation-based zero-waste baselines
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Youth culture and discipline at a school in the Western Cape
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Multilingual acoustic word embeddings for zero-resource languages
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Multilingual acquisition of determiner phrases in L2 English and L3 French by L1 Swahili speakers in Tanzania
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Neural networks in control engineering
Published 2023“…A study of feedforward topologies (one of the main classes of networks) shows that the multilayer perceptron network with its backpropagation training is well suited to model nonlinear mappings but fails to learn and generalize when subjected to slow varying training data. …”
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Development of a Low-Cost System for Monitoring Root Growth Dynamics
Published 2026Get full text
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