Run a focused checkpoint.
Answer what you know, skip what you do not, and let the run turn weak signals into a short review path.
Scope
Run at a glance
Starts with lower-friction anchors, then checks the concentration-to-learning-theory bridge.
Focused checkpoint
Ready for the checkpoint run?
Answer what you know and skip what you do not. Misses adjust the remaining order, and the result becomes a short review path for this checkpoint.
Probability / concentration bridge
A curated 10-question diagnostic bridge from sub-Gaussian tails through finite-class uniform convergence.
Learner can connect MGF assumptions, Hoeffding-style finite-sum bounds, ERM generalization gaps, and finite-class uniform convergence.
How this run adapts
Review focus
- sub-Gaussian MGF assumptions
- Hoeffding versus Chebyshev scope
- finite union bound in learning theory
- uniform convergence prerequisites
Could unlock
- Confidence-radius widget
- Finite ERM sample-size planner
Optional self-check
Leave blank if you want the neutral ramp. Pick only the areas where you have a strong signal.
Vectors, matrices, derivatives, notation.
Distributions, estimators, likelihood, concentration.
Gradients, convexity, SGD, Adam, proximal ideas.
ERM, VC, PAC, Rademacher, generalization.
Deep nets, attention, transformers, value functions.
Moving ideas across topics and checking assumptions.
This focused run uses the gold questions attached to the checkpoint. Sign in to attach it to your profile.
Browser-only run
This diagnostic will save for this browser, but it will not create account-level learning events. Sign in first if you want the run to count toward your profile.