Do not forget: Full memory in memory-based learning of word pronunciation

Memory-based learning, keeping full memory of learning material, appears a viable approach to learning NLP tasks, and is often superior in generalisation accuracy to eager learning approaches that abstract from learning material. Here we investigate three partial memory-based learning approaches which remove from memory specific task instance types estimated to be exceptional. The three approaches each implement one heuristic function for estimating exceptionality of instance types: (i) typicality, (ii) class prediction strength, and (iii) friendly-neighbourhood size. Experiments are performed with the memory-based learning algorithm IB1-IG trained on English word pronunciation. We find that removing instance types with low prediction strength (ii) is the only tested method which does not seriously harm generalisation accuracy. We conclude that keeping full memory of types rather than tokens, and excluding minority ambiguities appear to be the only performance-preserving optimisations of memory-based learning.Comment: uses conll98, epsf, and ipamacs (WSU IPA

Normalization by Evaluation with Typed Abstract Syntax

We present a simple way to implement typed abstract syntax for thelambda calculus in Haskell, using phantom types, and we specify normalization by evaluation (i.e., type-directed partial evaluation) to yield thistyped abstract syntax. Proving that normalization by evaluation preserves types and yields normal forms then reduces to type-checking thespecification

Convex Cycle Bases

Convex cycles play a role e.g. in the context of product graphs. We introduce convex cycle bases and describe a polynomial-time algorithm that recognizes whether a given graph has a convex cycle basis and provides an explicit construction in the positive case. Relations between convex cycles bases and other types of cycles bases are discussed. In particular we show that if G has a unique minimal cycle bases, this basis is convex. Furthermore, we characterize a class of graphs with convex cycles bases that includes partial cubes and hence median graphs. (authors' abstract)Series: Research Report Series / Department of Statistics and Mathematic

Constrained abstract representation problems in semigroups and partial groupoids

In this paper different constrained abstract representation theorems for partial groupoids and semigroups are proved. Methods for improving the retract properties of the structures are also developed. These have strong class-theoretical implications for many types of generalized periodic semigroups and related partial semigroups. The results are significant in a model-theoretical setting

A Simple Take on Typed Abstract Syntax in Haskell-like Languages

We present a simple way to program typed abstract syntax in a language following a Hindley-Milner typing discipline, such as Haskell and ML, and we apply it to automate two proofs about normalization functions as embodied in type-directed partial evaluation for the simply typed lambda calculus: normalization functions (1) preserve types and (2) yield long beta-eta normal forms.Keywords: Type-directed partial evaluation, normalization functions, simply-typed lambda-calculus, higher-order abstract syntax, Haskell

Operational Semantics of Resolution and Productivity in Horn Clause Logic

This paper presents a study of operational and type-theoretic properties of different resolution strategies in Horn clause logic. We distinguish four different kinds of resolution: resolution by unification (SLD-resolution), resolution by term-matching, the recently introduced structural resolution, and partial (or lazy) resolution. We express them all uniformly as abstract reduction systems, which allows us to undertake a thorough comparative analysis of their properties. To match this small-step semantics, we propose to take Howard's System H as a type-theoretic semantic counterpart. Using System H, we interpret Horn formulas as types, and a derivation for a given formula as the proof term inhabiting the type given by the formula. We prove soundness of these abstract reduction systems relative to System H, and we show completeness of SLD-resolution and structural resolution relative to System H. We identify conditions under which structural resolution is operationally equivalent to SLD-resolution. We show correspondence between term-matching resolution for Horn clause programs without existential variables and term rewriting.Comment: Journal Formal Aspect of Computing, 201