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- Linear Time Complexity Description: Linear time complexity is a measure that describes the time an algorithm takes to execute based on the size of the input data. It(...) Read more
- Logic Models Description: Logic models are fundamental tools in the field of explainable artificial intelligence (XAI), as they use logical statements to(...) Read more
- Linear Models Description: Linear models are statistical tools that establish a direct and proportional relationship between input variables and the output(...) Read more
- Local Interpretability Description: Local interpretability refers to the ability to explain individual predictions made by an artificial intelligence (AI) model.(...) Read more
- Linguistic Summary Description: The 'Linguistic Summary' in the context of explainable AI refers to the ability of an artificial intelligence model to provide a(...) Read more
- Learning Theory Description: The Learning Theory is a theoretical framework that studies how algorithms learn from data. This approach focuses on the ability of(...) Read more
- Local Model Description: The 'Local Model' refers to an approach in training artificial intelligence (AI) models that focuses on a specific subset of data,(...) Read more
- Local Training Description: Local training in the context of Federated Learning refers to the practice of training machine learning models using data that(...) Read more
- Learning Rate Schedule Description: The Learning Rate Schedule is a fundamental strategy in training neural networks that allows for the dynamic adjustment of the(...) Read more
- Local Aggregation Description: Local Aggregation is a fundamental process in the context of Federated Learning, referring to the combination of updates from(...) Read more
- Local Update Description: Local Update in the context of federated learning refers to a process where a machine learning model is trained using data residing(...) Read more
- Local Privacy Description: Local privacy is a fundamental concept in the field of federated learning, referring to the ability to ensure that users' local(...) Read more
- Learning Objective Description: The learning objective is the purpose that a machine learning algorithm seeks to achieve during its training process. This(...) Read more
- Learning Framework Description: The Learning Framework in the context of Federated Learning refers to a structured approach that provides guidelines and principles(...) Read more
- Local Feedback Description: Local feedback in the context of federated learning refers to the information and data generated and processed on a specific device(...) Read more
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