Hyperparameters are critical in machine learning , as different hyperparameters often result in models with significantly different performance. Hyperparameters may be deemed confidential because of their commercial value and the confidentiality of the proprietary algorithms that the learner uses to learn th...
Zip files (containing resnet-34 pytorch checkpoint.pth.tar, hyperparameters and training logs): Caltech256(Accuracy = 78.4%) CUBS200(77.1%) Indoor67(76.0%) Diabetic5(59.4%) #Format:$ python knockoff/victim/train.py DS_NAME ARCH -d DEV_ID \ -o models/victim/VIC_DIR -e EPOCHS --pret...
Zip files (containing pytorch checkpoint, transferset pickle file, hyperparameters and logs) can be downloaded using the links below. Specifically, the knockoffs are resnet34s at B=60k using imagenet as the query set ($P_A$). $F_V$RandomAdaptive Caltech256 zip (76.0%) zip (%) CUBS...