Rational series and their languages
Rational series and their languages
How to find the best approximation results
ACM SIGACT News
Minimization algorithms for sequential transducers
Theoretical Computer Science
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
The suffix Tree of a Tree and Minimizing Sequential Transducers
CPM '96 Proceedings of the 7th Annual Symposium on Combinatorial Pattern Matching
Finite-state transducers in language and speech processing
Computational Linguistics
Parameter estimation for probabilistic finite-state transducers
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Incremental construction of minimal acyclic sequential transducers from unsorted data
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Minimizing Deterministic Weighted Tree Automata
Language and Automata Theory and Applications
Minimizing deterministic weighted tree automata
Information and Computation
Myhill--Nerode type theory for fuzzy languages and automata
Fuzzy Sets and Systems
Learning deterministically recognizable tree series: revisited
CAI'07 Proceedings of the 2nd international conference on Algebraic informatics
Myhill-Nerode theorem for recognizable tree series revisited
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
On computability and some decision problems of parametric weighted finite automata
Journal of Automata, Languages and Combinatorics
How to train your multi bottom-up tree transducer
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Pushing for weighted tree automata
MFCS'11 Proceedings of the 36th international conference on Mathematical foundations of computer science
A coalgebraic perspective on linear weighted automata
Information and Computation
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Previous work on minimizing weighted finite-state automata (including transducers) is limited to particular types of weights. We present efficient new minimization algorithms that apply much more generally, while being simpler and about as fast.We also point out theoretical limits on minimization algorithms. We characterize the kind of "well-behaved" weight semirings where our methods work. Outside these semirings, minimization is not well-defined (in the sense of producing a unique minimal automaton), and even finding the minimum number of states is in general NP-complete and inapproximable.