Essays about: "Efficient Computation"
Showing result 1 - 5 of 146 essays containing the words Efficient Computation.
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1. Utilizing energy-saving techniques to reduce energy and memory consumption when training machine learning models : Sustainable Machine Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Emerging machine learning (ML) techniques are showing great potential in prediction performance. However, research and development is often conducted in an environment with extensive computational resources and blinded by prediction performance. READ MORE
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2. Decoding the surface code using graph neural networks
University essay from Göteborgs universitet / Institutionen för fysikAbstract : Quantum error correction is essential to achieve fault-tolerant quantum computation in the presence of noisy qubits. Among the most promising approaches to quantum error correction is the surface code, thanks to a scalable two-dimensional architecture, only nearest-neighbor interactions, and a high error threshold. Decoding the surface code, i.e. READ MORE
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3. Computationally Efficient Explainable AI: Bayesian Optimization for Computing Multiple Counterfactual Explanantions
University essay from KTH/Matematik (Avd.)Abstract : In recent years, advanced machine learning (ML) models have revolutionized industries ranging from the healthcare sector to retail and E-commerce. However, these models have become increasingly complex, making it difficult for even domain experts to understand and retrace the model's decision-making process. READ MORE
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4. Over-the-Air Federated Learning with Compressed Sensing
University essay from Linköpings universitet/KommunikationssystemAbstract : The rapid progress with machine learning (ML) technology has solved previously unsolved problems, but training these ML models requires ever larger datasets and increasing amounts of computational resources. One potential solution is to enable parallelization of the computations and allow local processing of training data in distributed nodes, such as Federated Learning (FL). READ MORE
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5. Artificial Neural Networks for Financial Time Series Prediction
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Financial market forecasting is a challenging and complex task due to the sensitivity of the market to various factors such as political, economic, and social factors. However, recent advances in machine learning and computation technology have led to an increased interest in using deep learning for forecasting financial data. READ MORE
