• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 12,577
Next 10 →

A Transformation System for Developing Recursive Programs

by R. M. Burstall, John Darlington , 1977
"... A system of rules for transforming programs is described, with the programs in the form of recursion equations An initially very simple, lucid. and hopefully correct program IS transformed into a more efficient one by altering the recursion structure Illustrative examples of program transformations ..."
Abstract - Cited by 649 (3 self) - Add to MetaCart
A system of rules for transforming programs is described, with the programs in the form of recursion equations An initially very simple, lucid. and hopefully correct program IS transformed into a more efficient one by altering the recursion structure Illustrative examples of program transformations

Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging

by Eric Brill - Computational Linguistics , 1995
"... this paper, we will describe a simple rule-based approach to automated learning of linguistic knowledge. This approach has been shown for a number of tasks to capture information in a clearer and more direct fashion without a compromise in performance. We present a detailed case study of this learni ..."
Abstract - Cited by 924 (8 self) - Add to MetaCart
this paper, we will describe a simple rule-based approach to automated learning of linguistic knowledge. This approach has been shown for a number of tasks to capture information in a clearer and more direct fashion without a compromise in performance. We present a detailed case study

A-morphous morphology

by Stephen R. Anderson, D. Meyer, D. Platt, D. Ridley , 1992
"... In the early years of the development of a theory of generative grammar (roughly 1955 through the early 1970s), a striking difference between the research problems that characterized the emerging field and those that had occupied its predecessors was the precipitous decline of the study of morpholog ..."
Abstract - Cited by 444 (9 self) - Add to MetaCart
of morphology. The principles of word structure can be divided roughly between those that govern the distribution of "morphemes " or subconstituents of a word and those that govern the variations in shape shown by these elements; and early developments in phonology and syntax left little if any

Representing Moving Images with Layers

by John Y.A. Wang, Edward H. Adelson , 1994
"... We describe a system for representing moving images with sets of overlapping layers. Each layer contains an intensity map that defines the additive values of each pixel, along with an alpha map that serves as a mask indicating the transparency. The layers are ordered in depth and they occlude each o ..."
Abstract - Cited by 542 (11 self) - Add to MetaCart
other in accord with the rules of compositing. Velocity maps define how the layers are to be warped over time. The layered representation is more flexible than standard image transforms and can capture many important properties of natural image sequences. We describe some methods for decomposing image

Factor Graphs and the Sum-Product Algorithm

by Frank R. Kschischang, Brendan J. Frey, Hans-Andrea Loeliger - IEEE TRANSACTIONS ON INFORMATION THEORY , 1998
"... A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple c ..."
Abstract - Cited by 1791 (69 self) - Add to MetaCart
computational rule, the sum-product algorithm operates in factor graphs to compute---either exactly or approximately---various marginal functions by distributed message-passing in the graph. A wide variety of algorithms developed in artificial intelligence, signal processing, and digital communications can

Computing with Membranes

by Gheorghe Păun - JOURNAL OF COMPUTER AND SYSTEM SCIENCES , 1998
"... We introduce a new computability model, of a distributed parallel type, based on the notion of a membrane structure. Such a structure consists of several cell-like membranes, recurrently placed inside a unique "skin" membrane. A plane representation is a Venn diagram without intersected se ..."
Abstract - Cited by 441 (5 self) - Add to MetaCart
sets and with a unique superset. In the regions delimited by the membranes there are placed objects; the obtained construct is called a super-cell. These objects are assumed to evolve: each object can be transformed in other objects, can pas through a membrane, or can disolve the membrane in which

Optimality Theory

by René Kager, Jason Eisner , 2000
"... Introduction Rene Kager's textbook is one of the first to cover Optimality Theory (OT), a declarative grammar framework that swiftly took over phonology after it was introduced by Prince, Smolensky, and McCarthy in 1993. OT reclaims traditional grammar's ability to express surface genera ..."
Abstract - Cited by 426 (2 self) - Add to MetaCart
generalizations ("syllables have onsets," "no nasal+voiceless obstruent clusters"). Empirically, some surface generalizations are robust within a language, or---perhaps for functionalist reasons--- widespread across languages. Derivational theories were forced to posit diverse rules

On Language and Connectionism: Analysis of a Parallel Distributed Processing Model of Language Acquisition

by Steven Pinker, Alan Prince - COGNITION , 1988
"... Does knowledge of language consist of mentally-represented rules? Rumelhart and McClelland have described a connectionist (parallel distributed processing) model of the acquisition of the past tense in English which successfully maps many stems onto their past tense forms, both regular (walk/walked) ..."
Abstract - Cited by 415 (13 self) - Add to MetaCart
Does knowledge of language consist of mentally-represented rules? Rumelhart and McClelland have described a connectionist (parallel distributed processing) model of the acquisition of the past tense in English which successfully maps many stems onto their past tense forms, both regular (walk

Morphological grayscale reconstruction in image analysis: Applications and efficient algorithms

by Luc Vincent - IEEE Transactions on Image Processing , 1993
"... Morphological reconstruction is part of a set of image operators often referred to as geodesic. In the binary case, reconstruction simply extracts the connected components of a binary image I (the mask) which are \marked " by a (binary) image J contained in I. This transformation can be ext ..."
Abstract - Cited by 336 (3 self) - Add to MetaCart
Morphological reconstruction is part of a set of image operators often referred to as geodesic. In the binary case, reconstruction simply extracts the connected components of a binary image I (the mask) which are \marked " by a (binary) image J contained in I. This transformation can

What's in a Translation Rule?

by Michel Galley, Mark Hopkins, Kevin Knight, Daniel Marcu
"... We propose a theory that gives formal semantics to word-level alignments defined over parallel corpora. We use our theory to introduce a linear algorithm that can be used to derive from word-aligned, parallel corpora the minimal set of syntactically motivated transformation rules that explain human ..."
Abstract - Cited by 297 (40 self) - Add to MetaCart
We propose a theory that gives formal semantics to word-level alignments defined over parallel corpora. We use our theory to introduce a linear algorithm that can be used to derive from word-aligned, parallel corpora the minimal set of syntactically motivated transformation rules that explain human
Next 10 →
Results 1 - 10 of 12,577
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University