We propose a novel Black-box Efficient Testing (BET) method for CNN models. The core insight of BET is that CNNs are generally prone to be affected by�...
BTM: Black-Box Testing for DNN Based on Meta-Learning. Conference Paper. Oct 2023. Zhuangyu Zhang � Zhiyi Zhang � Ziyuan Wang � Zhiqiu Huang � View.
Dec 20, 2021 � In this paper, we investigate black-box input diversity metrics as an alternative to white-box coverage criteria.
Missing: BTM: Meta-
Connected Papers is a visual tool to help researchers and applied scientists find academic papers relevant to their field of work.
May 16, 2020 � This story introduces optimization-based meta-learning, which covers black-box Adaptation and optimization-Based Approaches.
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BTM: Black-Box Testing for DNN Based on Meta-Learning. Conference Paper. Oct 2023. Zhuangyu Zhang � Zhiyi Zhang � Ziyuan Wang � Zhiqiu Huang � View.
A Simple Neural APenAve Meta-Learner. Mishra, Rohaninejad, Chen, Abbeel. ICLR '18. HW 1: - implement data processing. - implement simple black-box meta-learner.
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Mar 5, 2021 � This paper addresses this issue by proposing the use of meta-learning to infer population-based black-box optimizers that can automatically adapt to specific�...
Missing: BTM: Testing
Apr 2, 2023 � For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai ...
Duration: 1:17:59
Posted: Apr 2, 2023
Duration: 1:17:59
Posted: Apr 2, 2023
Missing: BTM: Testing DNN
it generalizes to the test sets. 2.1 Black-Box Meta-Learning. One way of doing black-box meta-learning is to train a recurrent model, like a RNN or an LSTM.
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