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Found 3 papers, 1 papers with code
Testing the Channels of Convolutional Neural Networks
To understand and debug convolutional neural networks (CNNs) we propose techniques for testing the channels of CNNs.
Gradient Estimation for Unseen Domain Risk Minimization with Pre-Trained Models
Although the task-specific knowledge could be learned from source domains by fine-tuning, this hurts the generalization power of pre-trained models due to gradient bias toward the source domains.
Reliable Decision from Multiple Subtasks through Threshold Optimization: Content Moderation in the Wild
In this study, we formulate real-world scenarios of content moderation and introduce a simple yet effective threshold optimization method that searches the optimal thresholds of the multiple subtasks to make a reliable moderation decision in a cost-effective way.
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