Fuzhou
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TabularBench: Benchmarking Adversarial Robustness for Tabular Deep Learning in Real-world Use-cases
We evaluated adversarial robustness with CAA, an ensemble of gradient and search attacks which was recently demonstrated as the most effective attack against a tabular model.
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TFGDA: Exploring Topology and Feature Alignment in Semi-supervised Graph Domain Adaptation through Robust Clustering Jun Dan
To achieve a stable alignment of feature distributions, we also introduce a SDA strategy to mitigate domain discrepancy on the sphere.
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Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.96)
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- Asia > China > Fujian Province > Fuzhou (0.06)
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PerturbationLearningBasedAnomalyDetection
There are a few approaches to building deep anomaly detection objectives or models.
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