Aggregated Learning
Aggregated Learning
**Aggregated Learning (AgrLearn)** is a vector-quantization approach to learning neural network classifiers. It builds on an equivalence between IB learning and IB quantization and exploits the power of vector quantization, which is well known in information theory.
Aggregated Learning: A Vector-Quantization Approach to Learning Neural Network Classifiers
https://paperswithcode.com/paper/aggregated-learning-a-vector-quantization
Aggregated Learning: A Vector-Quantization Approach to Learning Neural Network Classifiers