High Accuracy
High accuracy in machine learning models is a central research objective, focusing on improving the precision and reliability of predictions across diverse applications. Current efforts concentrate on developing efficient algorithms and architectures, such as deep neural networks, ensemble methods, and spiking neural networks, to achieve high accuracy while addressing limitations like memory constraints, computational cost, and data scarcity. These advancements are crucial for improving the performance of various systems, from speech recognition and natural language processing to medical image analysis and resource-limited device applications.
Papers
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