Title: Quiz Ch 11
Course: Machine Learning Security - Winter WC > Section: Unit 12

Q: Which activation function makes the network self-normalize?
- SELU
- Leaky ReLU
- ReLU
- GELU
A: SELU

Q: Which activation function is a tanh of softplus?
- Mish
- GELU
- SELU
- Swish
A: Mish

Q: Which technique prevents vanishing gradients by adding a layer to adjusst the inputs before each hidden layer?
- Batch normalization
- Gradient clipping
- Transfer learning
- Unsupervised pretraining
A: Batch normalization

Q: Which method is like a bowling ball rolling down a hill?
- Momentum
- Nesterov accelerated gradient
- AdaGrad
- RMSProp
A: Momentum

Q: What method trains only one layer at a time, and is no longer used?
- Greedy layer-wise pretraining
- Pretraining on an auxliary task
- Unsupervised pretraining
- Gradient clipping
A: Greedy layer-wise pretraining