Results 1 - 10 of 8,750

A Bayesian method for the induction of probabilistic networks from data

by Gregory F. Cooper, EDWARD HERSKOVITS - MACHINE LEARNING , 1992
"... This paper presents a Bayesian method for constructing probabilistic networks from databases. In particular, we focus on constructing Bayesian belief networks. Potential applications include computer-assisted hypothesis testing, automated scientific discovery, and automated construction of probabili ..."
Abstract - Cited by 1400 (31 self) - Add to MetaCart
of probabilistic expert systems. We extend the basic method to handle missing data and hidden (latent) variables. We show how to perform probabilistic inference by averaging over the inferences of multiple belief networks. Results are presented of a preliminary evaluation of an algorithm for constructing a belief

The inductive approach to verifying cryptographic protocols

by Lawrence C. Paulson - Journal of Computer Security , 1998
"... Informal arguments that cryptographic protocols are secure can be made rigorous using inductive definitions. The approach is based on ordinary predicate calculus and copes with infinite-state systems. Proofs are generated using Isabelle/HOL. The human effort required to analyze a protocol can be as ..."
Abstract - Cited by 480 (29 self) - Add to MetaCart
Informal arguments that cryptographic protocols are secure can be made rigorous using inductive definitions. The approach is based on ordinary predicate calculus and copes with infinite-state systems. Proofs are generated using Isabelle/HOL. The human effort required to analyze a protocol can

Least angle regression

by Bradley Efron, Trevor Hastie, Iain Johnstone, Robert Tibshirani , 2004
"... The purpose of model selection algorithms such as All Subsets, Forward Selection and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will be applied. Typically we have available a large collection of possible covariates from which we hope to s ..."
Abstract - Cited by 1326 (37 self) - Add to MetaCart
The purpose of model selection algorithms such as All Subsets, Forward Selection and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will be applied. Typically we have available a large collection of possible covariates from which we hope

Control-Flow Analysis of Higher-Order Languages

by Olin Shivers , 1991
"... representing the official policies, either expressed or implied, of ONR or the U.S. Government. Keywords: data-flow analysis, Scheme, LISP, ML, CPS, type recovery, higher-order functions, functional programming, optimising compilers, denotational semantics, nonstandard Programs written in powerful, ..."
Abstract - Cited by 365 (10 self) - Add to MetaCart
optimisations that depend upon data-flow analysis: common-subexpression elimination, loop-invariant detection, induction-variable elimination, and many, many more. Compilers for higherorder languages do not provide these optimisations. Without them, Scheme, LISP and ML compilers are doomed to produce code

Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure

by M. Hashem Pesaran , 2004
"... This paper presents a new approach to estimation and inference in panel data models with a multifactor error structure where the unobserved common factors are (possibly) correlated with exogenously given individual-specific regressors, and the factor loadings differ over the cross section units. The ..."
Abstract - Cited by 383 (44 self) - Add to MetaCart
. The basic idea behind the proposed estimation procedure is to filter the individual-specific regressors by means of (weighted) cross-section aggregates such that asymptotically as the cross-section dimension ( N) tends to infinity the differential effects of unobserved common factors are eliminated

Constraint Query Languages

by Paris C. Kanellakis , Gabriel M. Kuper, Peter Z. Revesz , 1992
"... We investigate the relationship between programming with constraints and database query languages. We show that efficient, declarative database programming can be combined with efficient constraint solving. The key intuition is that the generalization of a ground fact, or tuple, is a conjunction ..."
Abstract - Cited by 372 (43 self) - Add to MetaCart
of constraints over a small number of variables. We describe the basic Constraint Query Language design principles and illustrate them with four classes of constraints: real polynomial inequalities, dense linear order inequalities, equalities over an infinite domain, and boolean equalities. For the analysis

Branch-and-price: Column generation for solving huge integer programs

by Cynthia Barnhart, Ellis L. Johnson, George L. Nemhauser, Martin W. P. Savelsbergh, Pamela H. Vance - OPER. RES , 1998
"... We discuss formulations of integer programs with a huge number of variables and their solution by column generation methods, i.e., implicit pricing of nonbasic variables to generate new columns or to prove LP optimality at a node of the branch-and-bound tree. We present classes of models for which t ..."
Abstract - Cited by 360 (13 self) - Add to MetaCart
We discuss formulations of integer programs with a huge number of variables and their solution by column generation methods, i.e., implicit pricing of nonbasic variables to generate new columns or to prove LP optimality at a node of the branch-and-bound tree. We present classes of models for which

Bucket Elimination: A Unifying Framework for Reasoning

by Rina Dechter
"... Bucket elimination is an algorithmic framework that generalizes dynamic programming to accommodate many problem-solving and reasoning tasks. Algorithms such as directional-resolution for propositional satisfiability, adaptive-consistency for constraint satisfaction, Fourier and Gaussian elimination ..."
Abstract - Cited by 298 (58 self) - Add to MetaCart
Bucket elimination is an algorithmic framework that generalizes dynamic programming to accommodate many problem-solving and reasoning tasks. Algorithms such as directional-resolution for propositional satisfiability, adaptive-consistency for constraint satisfaction, Fourier and Gaussian

A new approach to abstract syntax with variable binding

by Murdoch J. Gabbay, Andrew M. Pitts - Formal Aspects of Computing , 2002
"... Abstract. The permutation model of set theory with atoms (FM-sets), devised by Fraenkel and Mostowski in the 1930s, supports notions of ‘name-abstraction ’ and ‘fresh name ’ that provide a new way to represent, compute with, and reason about the syntax of formal systems involving variable-binding op ..."
Abstract - Cited by 287 (63 self) - Add to MetaCart
-binding operations. Inductively defined FM-sets involving the name-abstraction set former (together with Cartesian product and disjoint union) can correctly encode syntax modulo renaming of bound variables. In this way, the standard theory of algebraic data types can be extended to encompass signatures involving

Useless-variable elimination

by Mellon School Of, Olin Shivers - In proceedings of Workshop on Static Analysis of Equational, Functional and Logic Programs, Université Bordeaux I, LaBRI , 1990
"... sed in the loop. UVE is often useful to clean up after applying other code transformations, such as copy propagation or induction-variable elimination. For example, when we introduce a new variable to track an induction function on some basic induction variable, the basic variable frequently become ..."
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sed in the loop. UVE is often useful to clean up after applying other code transformations, such as copy propagation or induction-variable elimination. For example, when we introduce a new variable to track an induction function on some basic induction variable, the basic variable frequently
Results 1 - 10 of 8,750