Tagged “learning-theory”

3 posts.

All Model Architecture21 Training & Alignment22 Inference & Serving23 Agents & Orchestration12 Reasoning & Evaluation27 Safety, Security & Governance9 Platforms & Practice22

Reasoning & Evaluation 23 min

Clustering Has No Ground Truth: Impossibility, Validation, and What a Cluster Can Promise

In 2002 Jon Kleinberg proved that no clustering function can satisfy three properties almost everyone would ask for. Every algorithm is therefore a definition of what a cluster is, and every validation index is another definition…

clustering unsupervised-learning evaluation metrics ∑ ◫

Training & Alignment 26 min

The Bias-Variance Tradeoff Is a Special Case: Double Descent, Benign Overfitting, and Grokking

A network that fits ImageNet with randomly shuffled labels should not generalise on real ones. It does. That single experiment invalidated the textbook account of why machine learning works, and the three phenomena that replaced …

training-dynamics generalisation double-descent grokking ∑ ◫

Reasoning & Evaluation 24 min

The Curse of Dimensionality: Why Distances Stop Meaning Anything, and Why Learning Works Anyway

Scatter 1,000 random points in a 1,000-dimensional cube and the farthest one from a query is only about 12% farther away than the nearest. By that arithmetic nearest-neighbour search should be meaningless, and yet every vector da…

supervised-classical learning-theory embeddings vector-search ∑ ◫