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Search Results - aimed algorithms
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Aiming strategies for small central receiver systems
Published 2015Get full text
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The development and evaluation of an electronic serious game aimed at the education of core programming skills
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Algorithmic trading and the liquidity of the JSE
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An online learning algorithm for technical trading
Published 2020“…We use an adversarial expert based online learning algorithm to learn the optimal parameters required to maximise wealth trading zero-cost portfolio strategies. …”
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Algorithmic randomness on computable metric spaces and hyperspaces
Published 2016“…In this text we shall be focusing on generalizing Martin-Löf randomness to computable metric spaces with arbitrary measure (for examples of this type of generalization see Gács [14], Rojas and Hoyrup [15]. The aim of this generalization is to define algorithmic randomness on the hyperspace of non-empty compact subsets of a computable metric space, the study of which was first proposed by Barmpalias et al. [16] at the University of Florida in their work on the random closed subsets of the Cantor space. …”
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Optimized Security-aware VM placement algorithm
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An investigation of dead-zone pattern matching algorithms
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Diagnostic Algorithm for Accurate detection of breast carcinoma on ultrasound
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Classification of customer complaints using machine learning algorithms
Published 2025“…The algorithms are meant to classify each customer complaint into one of the thirteen possible Products. …”
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Cooperative search and rescue using a scheduling algorithm
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Exploration of reinforcement learning algorithms implemented in the Wrapslide environment
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Superconducting neural network using quantum-flux parametrons
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An algorithmic approach to the 2D oriented strip packing problem
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Fast implementations of block motion estimation algorithms in video encoders
Published 2015“…This research is aimed at designing and implementing novel fast algorithms for speeding up the encoding process. …”
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Instance space analysis for the generalized bin packing problem algorithms
Published 2026“…In particular, the relationship between the problem instance features and the algorithm performance is studied. The results indicate that the chosen features are able to explain the difficulty of the problem instances, highlighting the strengths and weaknesses of the various algorithms. …”
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Addressing deep reinforcement learning: empirical algorithm performance evaluations∗
Published 2025“…Overall, we aim to move toward the better evaluation of RL algorithms and contribute toward an increased sensitivity to a lack of scientific rigour [2, 3] in the field of machine learning.…”
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Greedy Algorithm and Model for Analysis of a Bus Fleet's Operations
Published 2019Get full text
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