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Learning from Noisy Labels with Deep Neural Networks: A Survey (TNNLS 2022)

Deep learning has achieved remarkable success in numerous domains with help from large amounts of big data. However, the quality of data labels is a concern because of the lack of high-quality labels in many real-world scenarios. As noisy labels …

Ada-Boundary: Accelerating DNN Training via Adaptive Boundary Batch Selection (Machine Learning 2020, (SCI Expanded, impact factor: 2.672)

Neural networks converge faster with help from a smart batch selection strategy. In this regard, we propose Ada-Boundary, a novel and simple adaptive batch selection algorithm that constructs an effective mini-batch according to the learning progress …