Lafferty, JohnOverview
Publication Timeline
Most widely held works about
John Lafferty
Most widely held works by
John Lafferty
Prediction and discovery : AMSIMSSIAM Joint Summer Research Conference, Machine and Statistical Learning : Prediction and Discovery, June 2529, 2006, Snowbird, Utah
by AMSIMSSIAM Joint Summer Research Conference Machine and Statistical Learning : Prediction and Discovery
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Book
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9 editions published in 2007 in English and held by 181 WorldCat member libraries worldwide
Language modeling for information retrieval
by W. Bruce Croft
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Book
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10 editions published between 2003 and 2011 in English and held by 139 WorldCat member libraries worldwide This book contains the first collection of papers addressing recent developments in the design of information retrieval systems using language modeling techniques. Language modeling approaches are used in a variety of other language technologies, such as speech recognition and machine translation, and the book shows that applications such as Web search, crosslingual search, filtering, and summarization can be described in the same formal framework. The book is intended primarily for researchers and advanced graduate students working in the language technologies areas of computer science or information science
DC 9/11 time of crisis
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Visual
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2 editions published in 2004 in English and held by 112 WorldCat member libraries worldwide Focuses on the difficult decisions and tasks faced by President George Bush and his staff on September 11, 2001 and the days following the attacks. Based on indepth interviews and extensive research. Recounts the tragic events from the moment Bush hears the news of the attacks to significant briefings with advisors. Chronicles national security meetings, links with Osama bin Laden and the al Qaeda network. Illustrates the Administrations strategy for responding both the the terrorists and the American people
Christmas child
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Visual
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1 edition published in 2010 in English and held by 105 WorldCat member libraries worldwide As Christmas draws near, Jack finds himself disconnecting from the holidays, his job, and ultimately his wife. His latest assignment as journalist takes him to Dallas, but a mysterious photograph draws him to the town of Clearwater, Texas. It is here he discovers the town's lifesized, intricately carved nativity. As Jack delves into the mysteries surrounding the nativity and its creator, he uncovers secrets from his past, reunites with the family he never knew, and returns to the love that never left him
Asunder
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Visual
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2 editions published in 2003 in English and held by 103 WorldCat member libraries worldwide Chance and his very pregnant wife Roberta happily board a Ferris wheel with their best friends Michael and his fashion designer wife Lauren when a freak accident strikes, and Roberta and the baby are killed. Michael and Lauren let Chance welcome him into their luxurious home to grieve. Soon Lauren reveals that she recently had a secret abortion because she did not know if the child was Michael's or Chance's. Griefstricken and jealous, Chance starts stalking Lauren and doing everything in his power to wreck her marriage
The haunted world of Edward D. Wood, Jr
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Visual
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1 edition published in 1997 in English and held by 12 WorldCat member libraries worldwide The story of Hollywood director, Edward D. Wood, Jr., accompanied by interviews with those who knew him and film clips
Grammatical trigrams : a probabilistic model of link grammar
by John Lafferty
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Book
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3 editions published in 1992 in English and held by 7 WorldCat member libraries worldwide Abstract: "In this paper we present a new class of language models. This class derives from link grammar, a contextfree formalism for the description of natural language. We describe an algorithm for determining maximumlikelihood estimates of the parameters of these models. The language models which we present differ from previous models based on stochastic contextfree grammars in that they are highly lexical. In particular, they include the familiar ngram models as a natural subclass. The motivation for considering this class is to estimate the contribution which grammar can make to reducing the relative entropy of natural language."
Inducing features of random fields
by Stephen Della Pietra
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Book
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1 edition published in 1995 in English and held by 5 WorldCat member libraries worldwide Abstract: "We present a technique for constructing random fields from a set of training samples. The learning paradigm builds increasingly complex fields by allowing potential functions, or features, that are supported by increasingly large subgraphs. Each feature has a weight that is trained by minimizing the KullbackLeibler divergence between the model and the empirical distribution of the training data. A greedy algorithm determines how features are incrementally added to the field and an iterative scaling algorithm is used to estimate the optimal values of the weights. The random field models and techniques introduced in this paper differ from those common to much of the computer vision literature in that the underlying random fields are nonMarkovian and have a large number of parameters that must be estimated. Relations to other learning approaches including decision trees and Boltzmann machines are given. As a demonstration of the method, we describe its application to the problem of automatic word classification in natural language processing."
A robust parsing algorithm for link grammars
by Dennis Grinberg
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Book
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1 edition published in 1995 in English and held by 5 WorldCat member libraries worldwide Abstract: "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 [sic], these techniques enable the algorithm to run efficiently with cubic worstcase 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. We placed a version of the robust parser on the Word [sic] Wide Web for experimentation. It can be reached at URL http://www.cs.cmu.edu/afs/cs.cmu.edu/project/link/www/robust.html. In this version there are some limitations such as the maximum length of a sentence in words and the maximum amount of memory the parser can use."
Level spacings for SL(2,p)
by John Lafferty
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Book
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3 editions published in 1997 in English and held by 5 WorldCat member libraries worldwide We investigate the eigenvalue spacing distributions for randomly generated 4regular Cayley graphs on SL2(Fp) by numerically calculating their spectra. We present strong evidence that the distributions are Poisson and hence do not follow the Gaussian orthogonal ensemble. Among the Cayley graphs of SL2(Fp) we consider are the new expander graphs recently discovered by Y. Shalom. In addition, we use a Markov chain method to generate random 4regular graphs and observe that the average eigenvalue spacings are closely approximated by the Wigner surmise
Ordered Binary Decision Diagrams and Minimal Trellises
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Book
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2 editions published in 1998 in English and held by 3 WorldCat member libraries worldwide Ordered binary decision diagrams (OBDDs) are graph based data structures for representing Boolean functions. They have found widespread use in computer aided design and in formal verification of digital circuits. Minimal trellises are graphical representations of error correcting codes that play a prominent role in coding theory. This paper establishes a close connection between these two graphical models, as follows. Let C be a binary code of length n, and let fc(x1, ..., xn) be the Boolean function that takes the value 0 at x1, ..., xn if and only if (x1, ..., xn)epsilonC. Given this natural one to one correspondence between Boolean functions and binary codes, we prove that the minimal proper trellis for a code C with minimum distance d> 1 is isomorphic to the single terminal OBDD for its Boolean indicator function fC(x1, ..., xn). Prior to this result, the extensive research during the past decade on binary decision diagrams in computer engineering and on minimal trellises in coding theory has been carried out independently. As outlined in this work, the realization that binary decision diagrams and minimal trellises are essentially the same data structure opens up a range of promising possibilities for transfer of ideas between these disciplines
A derivation of the insideoutside algorithm from the EM algorithm
by John Lafferty
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Book
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2 editions published in 2000 in English and held by 3 WorldCat member libraries worldwide Abstract: "This note is a technical supplement to [4]. The purpose is to show how the InsideOutside algorithm is a special case of the EM algorithm [3], and to derive the parameter update formulas."
A unificationgrammarbased approach to the statistical analysis of English
by Ezra W Black
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Book
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1 edition published in 1989 in English and held by 2 WorldCat member libraries worldwide Abstract: "An overview is given of a system currently under development for the statistical analysis of natural language. An account of the stochastic training algorithm is given, together with a discussion of the underlying unification grammar of English, and a presentation of initial results."
Duality and Auxiliary Functions for Bregman Distances (revised)
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2 editions published between 2001 and 2002 in English and held by 2 WorldCat member libraries worldwide In this paper, the authors formulate and prove a convex duality theorem for minimizing a general class of Bregman distances subject to linear constraints. The duality result is then used to derive iterative algorithms for solving the associated optimization problem. Their presentation is motivated by the recent work of Collins, Schapire, and Singer (2001), who showed how certain boosting algorithms and maximum likelihood logistic regression can be unified within the framework of Bregman distances. In particular, specific instances of the results given here are used by Collins et al. (2001) to show the convergence of a family of iterative algorithms for minimizing the exponential or logistic loss. Following an introduction, Section 2 recalls the standard definitions from convex analysis that will be required, and presents the technical assumptions made on the class of Bregman distances that the authors work with. They also introduce some new terminology, using the terms LegendreBregman conjugate and LegendreBregman projection to extend the classical notion of the Legendre conjugate and transform to Bregman distances. Section 3 contains the statement and proof of the duality theorem that connects the primal problem with its dual, showing that the solution is characterized in geometrical terms by a Pythagorean equality. Section 4 defines the notion of an auxiliary function, which is used to construct iterative algorithms for solving constrained optimization problems. This section shows how convexity can be used to derive an auxiliary function for Bregman distances based on separable functions. The last section summarizes the main results of the paper
Ordered binary decision diagrams and minimal trellises
by John Lafferty
(
Book
)
1 edition published in 1998 in English and held by 2 WorldCat member libraries worldwide Abstract: "Ordered binary decision diagrams (OBDDs) are graphbased data structures for representing Boolean functions. They have found widespread use in computeraided design and in formal verification of digital circuits. Minimal trellises are graphical representations of errorcorrecting codes that play a prominent role in coding theory. This paper establishes a close connection between these two graphical models, as follows. Let C be a binary code of length n, and let f[subscript c](x₁, ..., x[subscript n]) be the Boolean function that takes the value 0 at x₁, ..., x[subscript n] if and only if (x₁, ..., x[subscript n]) [element of] C. Given this natural onetoone correspondence between Boolean functions and binary codes, we prove that the minimal proper trellis for a code C with minimum distance d> 1 is isomorphic to the singleterminal OBDD for its Boolean indicator function f[subscript c](x₁, ..., x[subscript n]). Prior to this result, the extensive research during the past decade on binary decision diagrams  in computer engineering  and on minimal trellises  in coding theory  has been carried out independently. As outlined in this work, the realization that binary decision diagrams and minimal trellises are essentially the same data structure opens up a range of promising possibilities for transfer of ideas between these disciplines."
Duality and auxiliary functions for Bregman distances
by Stephen Della Pietra
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Book
)
2 editions published between 2001 and 2002 in English and held by 2 WorldCat member libraries worldwide Abstract: "We formulate and prove a convex duality theorem for Bregman distances and present a technique based on auxiliary functions for deriving and proving convergence of iterative algorithms to minimize Bregman distance subject to linear constraints."
Basic methods of probabilistic context free grammars
by Frederick Jelinek
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Book
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1 edition published in 1990 in English and held by 2 WorldCat member libraries worldwide We introduce four classes of algorithms that handle PCFGs: (1) Computation of the total probability that a PCFG generates a given sentence; (2) Method of finding the most probable parse tree of a given sentence; (3) Estimation of probabilities of rewriting rules of a PCFG on the basis of a text corpus; (4) Computation of the probability that the PCFG produces a sentence having a given initial substring."
Diffusion kernels on statistical manifolds
by John Lafferty
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Book
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1 edition published in 2004 in English and held by 1 WorldCat member library worldwide Abstract: "A family of kernels for statistical learning is introduced that exploits the geometric structure of statistical models. The kernels are based on the heat equation on the Riemannian manifold defined by the Fisher information metric associated with a statistical family, and generalize the Gaussian kernel of Euclidean space. As an important special case, kernels based on the geometry of multinomial families are derived, leading to kernelbased learning algorithms that apply naturally to discrete data. Bounds on covering numbers and Rademacher averages for the kernels are proved using bounds on the eigenvalues of the Laplacian on Riemannian manifolds. Experimental results are presented for document classification, for which the use of multinomial geometry is natural and well motivated, and improvements are obtained over the standard use of Gaussian or linear kernels, which have been the standard for text classification."
Semisupervised learning : from Gaussian fields to Gaussian processes
by Xiaojin Zhu
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Book
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1 edition published in 2003 in English and held by 1 WorldCat member library worldwide Abstract: "We show that the Gaussian random fields and harmonic energy minimizing function framework for semisupervised learning can be viewed in terms of Gaussian processes, with covariance matrices derived from the graph Laplacian. We derive hyperparameter learning with evidence maximization, and give an empirical study of various ways to parameterize the graph weights."
GibbsMarkov models
by John Lafferty
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1 edition published in 1996 in English and held by 1 WorldCat member library worldwide more
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Adoption Adultery Algorithms ArmiesOfficers Artificial intelligence Automatic speech recognition Bereavement Bush, George W.(George Walker), CaliforniaIone Christmas plays Coding theory Computational linguistics Computer science Convexity spaces Crèches (Nativity scenes) Data structures (Computer science) Decision trees Eigenvalues Families Friendship Functions, Zeta Heat equation Husband and wife Information retrieval Information storage and retrieval systems Iterative methods (Mathematics) Journalists Kernel functions Lafferty, John Legendre's functions Linguistic models Love Machine learning Machine theory Manwoman relationships Married people Mathematical optimization Motion picture producers and directors National security Natural language processing (Computer science) Parsing (Computer grammar) Poisson distribution Preston School of Industry (Ione, Calif.) Random fields Random matrices Reformatories September 11 Terrorist Attacks (2001) Texas United States Wood, Edward D.(Edward Davis),

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