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Published 20 hours ago • verified publisher icon whyisyoung
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Code for our USENIX Security 2021 paper -- CADE: Detecting and Explaining Concept Drift Samples for Security Applications

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No gradients provided for any variable: {variable}

Traceback (most recent call last): File "test_cade.py", line 66, in cae.train(train_dataX_np, y_train, cae_lambda_1, cae_batch_size, cae_epochs, cae_similar_ratio, cae_margin, File "/home/lhd/uncertainity_malware/OOD/cade/autoencoder.py", line 315, in train train_op = self.optimizer.minimize(loss=lambda: loss, var_list=tf.compat.v1.trainable_variables()) File "/home/lhd/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py",...

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Code for our USENIX Security 2021 paper -- CADE: Detecting and Explaining Concept Drift Samples for Security Applications

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