19,893 research outputs found
Simulation of Two-Way Pushdown Automata Revisited
The linear-time simulation of 2-way deterministic pushdown automata (2DPDA)
by the Cook and Jones constructions is revisited. Following the semantics-based
approach by Jones, an interpreter is given which, when extended with
random-access memory, performs a linear-time simulation of 2DPDA. The recursive
interpreter works without the dump list of the original constructions, which
makes Cook's insight into linear-time simulation of exponential-time automata
more intuitive and the complexity argument clearer. The simulation is then
extended to 2-way nondeterministic pushdown automata (2NPDA) to provide for a
cubic-time recognition of context-free languages. The time required to run the
final construction depends on the degree of nondeterminism. The key mechanism
that enables the polynomial-time simulations is the sharing of computations by
memoization.Comment: In Proceedings Festschrift for Dave Schmidt, arXiv:1309.455
Tabular Parsing
This is a tutorial on tabular parsing, on the basis of tabulation of
nondeterministic push-down automata. Discussed are Earley's algorithm, the
Cocke-Kasami-Younger algorithm, tabular LR parsing, the construction of parse
trees, and further issues.Comment: 21 pages, 14 figure
If the Current Clique Algorithms are Optimal, so is Valiant's Parser
The CFG recognition problem is: given a context-free grammar
and a string of length , decide if can be obtained from
. This is the most basic parsing question and is a core computer
science problem. Valiant's parser from 1975 solves the problem in
time, where is the matrix multiplication
exponent. Dozens of parsing algorithms have been proposed over the years, yet
Valiant's upper bound remains unbeaten. The best combinatorial algorithms have
mildly subcubic complexity.
Lee (JACM'01) provided evidence that fast matrix multiplication is needed for
CFG parsing, and that very efficient and practical algorithms might be hard or
even impossible to obtain. Lee showed that any algorithm for a more general
parsing problem with running time can
be converted into a surprising subcubic algorithm for Boolean Matrix
Multiplication. Unfortunately, Lee's hardness result required that the grammar
size be . Nothing was known for the more relevant
case of constant size grammars.
In this work, we prove that any improvement on Valiant's algorithm, even for
constant size grammars, either in terms of runtime or by avoiding the
inefficiencies of fast matrix multiplication, would imply a breakthrough
algorithm for the -Clique problem: given a graph on nodes, decide if
there are that form a clique.
Besides classifying the complexity of a fundamental problem, our reduction
has led us to similar lower bounds for more modern and well-studied cubic time
problems for which faster algorithms are highly desirable in practice: RNA
Folding, a central problem in computational biology, and Dyck Language Edit
Distance, answering an open question of Saha (FOCS'14)
A Robust Parsing Algorithm For Link Grammars
In this paper we present a robust parsing algorithm based on the link grammar
formalism for parsing natural languages. Our algorithm is a natural extension
of the original dynamic programming recognition algorithm which recursively
counts the number of linkages between two words in the input sentence. The
modified algorithm uses the notion of a null link in order to allow a
connection between any pair of adjacent words, regardless of their dictionary
definitions. The algorithm proceeds by making three dynamic programming passes.
In the first pass, the input is parsed using the original algorithm which
enforces the constraints on links to ensure grammaticality. In the second pass,
the total cost of each substring of words is computed, where cost is determined
by the number of null links necessary to parse the substring. The final pass
counts the total number of parses with minimal cost. All of the original
pruning techniques have natural counterparts in the robust algorithm. When used
together with memoization, these techniques enable the algorithm to run
efficiently with cubic worst-case complexity. We have implemented these ideas
and tested them by parsing the Switchboard corpus of conversational English.
This corpus is comprised of approximately three million words of text,
corresponding to more than 150 hours of transcribed speech collected from
telephone conversations restricted to 70 different topics. Although only a
small fraction of the sentences in this corpus are "grammatical" by standard
criteria, the robust link grammar parser is able to extract relevant structure
for a large portion of the sentences. We present the results of our experiments
using this system, including the analyses of selected and random sentences from
the corpus.Comment: 17 pages, compressed postscrip
Synchronous Context-Free Grammars and Optimal Linear Parsing Strategies
Synchronous Context-Free Grammars (SCFGs), also known as syntax-directed
translation schemata, are unlike context-free grammars in that they do not have
a binary normal form. In general, parsing with SCFGs takes space and time
polynomial in the length of the input strings, but with the degree of the
polynomial depending on the permutations of the SCFG rules. We consider linear
parsing strategies, which add one nonterminal at a time. We show that for a
given input permutation, the problems of finding the linear parsing strategy
with the minimum space and time complexity are both NP-hard
Cognitive visual tracking and camera control
Cognitive visual tracking is the process of observing and understanding the behaviour of a moving person. This paper presents an efficient solution to extract, in real-time, high-level information from an observed scene, and generate the most appropriate commands for a set of pan-tilt-zoom (PTZ) cameras in a surveillance scenario. Such a high-level feedback control loop, which is the main novelty of our work, will serve to reduce uncertainties in the observed scene and to maximize the amount of information extracted from it. It is implemented with a distributed camera system using SQL tables as virtual communication channels, and Situation Graph Trees for knowledge representation, inference and high-level camera control. A set of experiments in a surveillance scenario show the effectiveness of our approach and its potential for real applications of cognitive vision
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