Alphabeta Math

Linear contextual bandits and LinUCB — Examples

About this page
Pipeline-generated
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

✓ 4 results · all verified · 0 also independently AI-judged
Every result on this page is machine-checked by a proof checker and read in full and owner-audited; the judge is an additional, independent cross-model AI review of the proofs. The 4 not AI-judged were verified by owner audit (typically over a confirmed judge false positive), not failures.
1 · Prerequisites
Abstract Algebra
Bayesian Computational Statistics
Combinatorics
Coxeter Groups
Functional Analysis
Linear Algebra
Machine Learning Algorithms
Measure Theory
Number Theory
Probability
Real Analysis
Set Theory
Topology
2 · Logical flowchart

3 · Items

Example

A feature outside the assumed norm bound

Example

A two-context, two-action ridge update

Example

No common confidence radius without a parameter norm bound

Example

An action set whose linear-mean range exceeds one

Sources