Наредни састанак Семинара биће одржан онлајн у среду, 11. октобра 2023, са почетком у 19 часова.
Предавач: Johanna Björklund, Associate Professor, Department of Computing Science, Umeå University, Umeå, Sweden
Наслов предавања: THE IMPACT OF STATE MERGING ON PREDICTIVE ACCURACY IN PROBABILISTIC TREE AUTOMATA: DIETZE’S CONJECTURE REVISITED
Апстракт: Dietze’s conjecture concerns the problem of equipping a tree automaton M with weights to make it probabilistic, in such a way that the resulting automaton N predicts a given corpus C as accurately as possible. The conjecture states that the accuracy cannot increase if the states in M are first merged with respect to an equivalence relation on the state space, so that the result is a smaller automaton M’. Put differently, merging states can never improve predictions. This is under the assumption that both M and M’ are bottom-up deterministic and accept every tree in corpus. We prove that the conjecture holds, using a construction that turns any probabilistic version N’ of M’ into a probabilistic version N of M, such that N assigns at least as great a weight to each tree in C as N’ does.
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https://miteam.mi.sanu.ac.rs/asset/CW5nJWDSEZDj7p32p
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https://miteam.mi.sanu.ac.rs/asset/4LNW8WtML7rLKojoz