Essays about: "Models of Computation"
Showing result 1 - 5 of 195 essays containing the words Models of Computation.
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1. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks
University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)Abstract : In the era of data-driven decision-making and innovation, synthetic data serves as a promising tool that bridges the need for vast datasets in machine learning (ML) and the imperative necessity of data privacy. By simulating real-world data while preserving privacy, synthetic data generators have become more prevalent instruments in AI and ML development. READ MORE
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2. 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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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. Parameter Inference for Stochastic Models of Gene Expression in Eukaryotic Cells
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : Simulation models are often used to study a system or phenomenon. However, before a simulation model can be used, its parameter needs to be fit to mimic observed data. This is called the parameter inference problem. READ MORE
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5. Preserving Privacy in Cloud Services by Using an Explainable Deep-Learning Model for Anomaly Detection
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : As cloud services become increasingly popular, ensuring their privacy and security has become a significant concern for users. Cloud computing involves Data Service Outsourcing and Computation Outsourcing, which require additional security considerations compared to traditional computing. READ MORE