We consider the problem of PAC-learning distributions over strings, represented by probabilistic deterministic finite automata (PDFAs). PDFAs are a probabilistic model for the gen...
It is often useful for a robot to construct a spatial representation of its environment from experiments and observations, in other words, to learn a map of its environment by exp...
Thomas Dean, Dana Angluin, Kenneth Basye, Sean P. ...
Abstract. Recently, a number of authors have explored the use of recursive recursive neural nets (RNN) for the adaptive processing of trees or tree-like structures. One of the most...
Information extraction (IE) addresses the problem of extracting specific information from a collection of documents. Much of the previous work on IE from structured documents, suc...
Raymond Kosala, Hendrik Blockeel, Maurice Bruynoog...
Inthispaperweintroduceanondeterministiccounterpart to Reduced, Ordered Binary Decision Diagrams for the representation and manipulation of logic functions. ROBDDs are conceptually...