Algebra & AI
Essays at the seam
Pieces on the role of algebraic and order-theoretic structure inside machine learning — interpretability, preference, learning as closure.
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Concept lattices as interpretable models
Math + AIAppliedA concept lattice is, by construction, an interpretable artefact. What does it mean to use one as a model — and where does that view help, and where does it strain?
· Tom Hanika -
What Galois connections have to do with learning
Math + AIPureGalois connections are the algebraic skeleton inside Formal Concept Analysis. They are also, perhaps less obviously, the algebraic skeleton inside a number of learning algorithms — closure operators in disguise.
· Tom Hanika -
Order structure in preference data
Math + AIAppliedPreferences are partial orders, not real-valued scores. Most modern ML pipelines collapse them into scalars and lose much of what the labellers actually said. This essay works through the order-theoretic alternatives in detail.
· Tom Hanika