Search results for "Deterministic algorithm"
showing 7 items of 27 documents
Active Learning of Recursive Functions by Ultrametric Algorithms
2014
We study active learning of classes of recursive functions by asking value queries about the target function f, where f is from the target class. That is, the query is a natural number x, and the answer to the query is f(x). The complexity measure in this paper is the worst-case number of queries asked. We prove that for some classes of recursive functions ultrametric active learning algorithms can achieve the learning goal by asking significantly fewer queries than deterministic, probabilistic, and even nondeterministic active learning algorithms. This is the first ever example of a problem where ultrametric algorithms have advantages over nondeterministic algorithms.
Properties and application of nondeterministic quantum query algorithms
2006
Many quantum algorithms can be analyzed in a query model to compute Boolean functions where input is given by a black box. As in the classical version of decision trees, different kinds of quantum query algorithms are possible: exact, zero-error, bounded-error and even nondeterministic. In this paper, we study the latter class of algorithms. We introduce a fresh notion in addition to already studied nondeterministic algorithms and introduce dual nondeterministic quantum query algorithms. We examine properties of such algorithms and prove relations with exact and nondeterministic quantum query algorithm complexity. As a result and as an example of the application of discovered properties, we…
Causal Inference in Geoscience and Remote Sensing From Observational Data
2020
Establishing causal relations between random variables from observational data is perhaps the most important challenge in today’s science. In remote sensing and geosciences, this is of special relevance to better understand the earth’s system and the complex interactions between the governing processes. In this paper, we focus on an observational causal inference, and thus, we try to estimate the correct direction of causation using a finite set of empirical data. In addition, we focus on the more complex bivariate scenario that requires strong assumptions and no conditional independence tests can be used. In particular, we explore the framework of (nondeterministic) additive noise models, …
Descriptional and Computational Complexity of the Circuit Representation of Finite Automata
2018
In this paper we continue to investigate the complexity of the circuit representation of DFA—BC-complexity. We compare it with nondeterministic state complexity, obtain upper and lower bounds which differ only by a factor of 4 for a Binary input alphabet. Also we prove that many simple operations (determining if a state is reachable or if an automaton is minimal) are PSPACE-complete for DFA given in circuit representation.
An Approximate Determinization Algorithm for Weighted Finite-State Automata
2001
Nondeterministic weighted finite-state automata are a key abstraction in automatic speech recognition systems. The efficiency of automatic speech recognition depends directly on the sizes of these automata and the degree of nondeterminism present, so recent research has studied ways to determinize and minimize them, using analogues of classical automata determinization and minimization. Although, as we describe here, determinization can in the worst case cause poly-exponential blowup in the number of states of a weighted finite-state automaton, in practice it is remarkably successful. In extensive experiments in automatic speech recognition systems, deterministic weighted finite-state autom…
Tally languages accepted by Monte Carlo pushdown automata
1997
Rather often difficult (and sometimes even undecidable) problems become easily decidable for tally languages, i.e. for languages in a single-letter alphabet. For instance, the class of languages recognizable by 1-way nondeterministic pushdown automata equals the class of the context-free languages, but the class of the tally languages recognizable by 1-way nondeterministic pushdown automata, contains only regular languages [LP81]. We prove that languages over one-letter alphabet accepted by randomized one-way 1-tape Monte Carlo pushdown automata are regular. However Monte Carlo pushdown automata can be much more concise than deterministic 1-way finite state automata.
How to simulate free will in a computational device
1999
Since we believe that human brain is not a purely deterministic device merely reacting to the environment but rather it is capable to a free will, Theoretical Computer Science has also tried to develop a system of notions generalizing determinism. Nondeterministic and probabilistic algorithms were the first generalizations. Nondeterministic machines constitute an important part of the Theory of Computation. Nondeterminism is a useful way to describe possible choices. In real life there are many regulations restricting our behavior. These regulations nearly always leave some freedom for us how to react. Such regulations are best described in terms of nondeterministic algorithms. Nondetermini…