CS 7643 CS7643 Quiz 5 Latest

CS 7643 / CS7643 Quiz 5 (Latest Update 2025 / 2026) Deep Learning | Questions & Answers | Grade A | 100% Correct - Georgia Tech

Question:

Meta-Learning (Few-Shot Learning)

Answer:

• Learning to learn
• Learn NN initialization that after it perform SGD steps on small amounts of

labeled data, you learn an effective initialization

Question:

Surrogate Tasks (Self-Supervised Learning)

Answer:

• Identify loss functions for tasks we don't care about, but allow us to learn

good feature representations

• / 3

Question:

Multi-View Pseudo-Labeling Key Details for Success

Answer:

• Pseudo-labeling without augmentation isn't very effective

--> need good data augmentation algos

• Doing this in multiple stages isn't as good as end to end

• Large unlabeled batch sizes are necessary for the labels to be good
• Confidence threshold is very important

--> too big = not getting many labels, too small = many noisy examples

• Cosine learning rate schedules
• Inference with exponential moving average of weights

--> stabilizes training and improves performance

Question:

Other Methods for Semi-Supervised Learning

Answer:

MixMatch/ReMixMatch: More complex variations prior to FIxMatch

• Temperature scaling and entropy minimization to stabilize training
• Multiple augmentations and ensemblier to improve pseudo-labels

Virtual Adversarial Training: Augmentation through adversarial examples 2 / 3

Mean Teach: Student/teacher distillation consistency method with

exponential moving average

Question:

Label Propagation (Semi-supervised learning)

Answer:

• Learn feature extractors
• Use feature extractors on unlabeled examples

--> Uses clustering assumption so items close in feature space are labeled similarly

Question:

Few-Shot Learning Baseline

Answer:

• Train classifier on base classes and Fine Tune using small amounts of labeled

data for new classes

• Pretty good baseline compared to more sophisticated approaches

• / 3