
Dropout as Shared-Parameter Bagging
March 7, 2026
A concrete way to understand dropout in deep learning: sampled subnetworks with shared weights, standing in for a much more expensive ensemble.
Read postBook notes from Alex Leung, with a focus on deep learning, machine learning foundations, and technical reading.
3 posts currently filed under Book Notes.

A concrete way to understand dropout in deep learning: sampled subnetworks with shared weights, standing in for a much more expensive ensemble.
Read post
Goodfellow Chapter 6 sharpened how I separate representation, parameter efficiency, and optimization when thinking about deep feedforward networks.
Read post
Part I of Goodfellow, Bengio, and Courville works best as shared vocabulary for later chapters, with proof details still worth supplementing.
Read postCopyright © 2020 - 2026 Alex Leung