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Harnessing the Power of Explanations for Incremental Training: A LIME-Based Approach
In this work, model explanations are fed back to the feed-forward training to help the model generalize better.
A Fast Network Exploration Strategy to Profile Low Energy Consumption for Keyword Spotting
We propose a regression-based network exploration technique that considers the scaling of the network filters ($s$) and quantization ($q$) of the network layers, leading to a friendly and energy-efficient configuration for FPGA hardware implementation.
Neural Networks for Pulmonary Disease Diagnosis using Auditory and Demographic Information
Pulmonary diseases impact millions of lives globally and annually.
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