Classification Problem
Classification, the task of assigning data points to predefined categories, is a fundamental problem in machine learning with applications across diverse fields. Current research focuses on improving robustness to noisy or imbalanced data, exploring novel algorithms like those based on persistence kernels and optimal transport, and developing more efficient and interpretable models such as decision trees and improved neural network architectures. These advancements aim to enhance classification accuracy, reliability, and scalability, impacting areas ranging from medical diagnosis to software engineering and beyond.
Papers
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