arXiv subjects

Raphaela Palenta

Publications and source records attributed to Raphaela Palenta.

4 recordsLinked to original sources

arXiv2019

Deciding Equivalence of Separated Non-Nested Attribute Systems in Polynomial Time

In 1982, Courcelle and Franchi-Zannettacci showed that the equivalence problem of separated non-nested attribute systems can be reduced to the equivalence problem of total deterministic separated basic macro tree transducers. They also gave a procedure for deciding equivalence of transducer in the latter class. Here, we reconsider this equivalence problem. We present a new alternative decision procedure and prove that it runs in polynomial time. We also consider extensions of this result to partial transducers and to the case where parameters of transducers accumulate strings instead of trees.

cs.FL↗

arXiv2018

Computing the longest common prefix of a context-free language in polynomial time

We present two structural results concerning longest common prefixes of non-empty languages. First, we show that the longest common prefix of the language generated by a context-free grammar of size $N$ equals the longest common prefix of the same grammar where the heights of the derivation trees are bounded by $4N$. Second, we show that each nonempty language $L$ has a representative subset of at most three elements which behaves like $L$ w.r.t. the longest common prefix as well as w.r.t. longest common prefixes of $L$ after unions or concatenations with arbitrary other languages. From that, we conclude that the longest common prefix, and thus the longest common suffix, of a context-free language can be computed in polynomial time.

cs.FL↗

arXiv2016

Deciding Equivalence of Linear Tree-to-Word Transducers in Polynomial Time

We show that the equivalence of deterministic linear top-down tree-to-word transducers is decidable in polynomial time. Linear tree-to-word transducers are non-copying but not necessarily order-preserving and can be used to express XML and other document transformations. The result is based on a partial normal form that provides a basic characterization of the languages produced by linear tree-to-word transducers.

cs.FL↗

arXiv2014

A Map of Update Constraints in Inductive Inference

We investigate how different learning restrictions reduce learning power and how the different restrictions relate to one another. We give a complete map for nine different restrictions both for the cases of complete information learning and set-driven learning. This completes the picture for these well-studied \emph{delayable} learning restrictions. A further insight is gained by different characterizations of \emph{conservative} learning in terms of variants of \emph{cautious} learning. Our analyses greatly benefit from general theorems we give, for example showing that learners with exclusively delayable restrictions can always be assumed total.

cs.LG↗