Results 1 - 10 of 27,496

Feeling and thinking: Preferences need no inferences

by R. B. Zajonc - AMERICAN PSYCHOLOGIST , 1980
"... Affect is considered by most contemporary theories to be postcognitive, that is, to occur only after considerable cognitive operations have been accomplished. Yet a number of experimental results on preferences, attitudes, impression formation, and decision making, as well as some clinical phenomen ..."
Abstract - Cited by 596 (2 self) - Add to MetaCart
Affect is considered by most contemporary theories to be postcognitive, that is, to occur only after considerable cognitive operations have been accomplished. Yet a number of experimental results on preferences, attitudes, impression formation, and decision making, as well as some clinical

Bayesian density estimation and inference using mixtures.

by Michael D Escobar , Mike West - J. Amer. Statist. Assoc. , 1995
"... JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about J ..."
Abstract - Cited by 653 (18 self) - Add to MetaCart
, assessment of modality, and the inference on the numbers of components. Also, convergence results are established for a general class of normal mixture models. American Statistical Association

Searching Distributed Collections With Inference Networks

by James P. Callan, Zhihong Lu, W. Bruce Croft - IN PROCEEDINGS OF THE 18TH ANNUAL INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL , 1995
"... The use of information retrieval systems in networked environments raises a new set of issues that have received little attention. These issues include ranking document collections for relevance to a query, selecting the best set of collections from a ranked list, and merging the document rankings t ..."
Abstract - Cited by 471 (36 self) - Add to MetaCart
that are returned from a set of collections. This paper describes methods of addressing each issue in the inference network model, discusses their implementation in the INQUERY system, and presents experimental results demonstrating their effectiveness.

Loopy belief propagation for approximate inference: An empirical study. In:

by Kevin P Murphy , Yair Weiss , Michael I Jordan - Proceedings of Uncertainty in AI, , 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performanc ..."
Abstract - Cited by 676 (15 self) - Add to MetaCart
and ap proximately 4000 findin nodes, with a number of ob served findings that varies per case. Due to the form of the noisy-or CPTs the complexity of inference is ex ponential in the number of positive findings Results Initial experiments The experimental protocol for the PYRAMID network was as follows

A Bayesian Framework for the Analysis of Microarray Expression Data: Regularized t-Test and Statistical Inferences of Gene Changes

by Pierre Baldi, Anthony D. Long - Bioinformatics , 2001
"... Motivation: DNA microarrays are now capable of providing genome-wide patterns of gene expression across many different conditions. The first level of analysis of these patterns requires determining whether observed differences in expression are significant or not. Current methods are unsatisfactory ..."
Abstract - Cited by 491 (6 self) - Add to MetaCart
due to the lack of a systematic framework that can accommodate noise, variability, and low replication often typical of microarray data. Results: We develop a Bayesian probabilistic framework for microarray data analysis. At the simplest level, we model log-expression values by independent normal

Reasoning the fast and frugal way: Models of bounded rationality.

by Gerd Gigerenzer , Daniel G Goldstein - Psychological Review, , 1996
"... Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following H. Simon's notion of satisncing, the authors have ..."
Abstract - Cited by 611 (30 self) - Add to MetaCart
between the satisncing "Take The Best" algorithm and various "rational" inference procedures (e.g., multiple regression). The Take The Best algorithm matched or outperformed all competitors in inferential speed and accuracy. This result is an existence proof that cognitive mechanisms

Interpretation as Abduction

by Jerry R. Hobbs, Mark Stickel, Paul Martin, Douglas Edwards , 1990
"... An approach to abductive inference developed in the TACITUS project has resulted in a dramatic simplification of how the problem of interpreting texts is conceptualized. Its use in solving the local pragmatics problems of reference, compound nominals, syntactic ambiguity, and metonymy is described ..."
Abstract - Cited by 687 (38 self) - Add to MetaCart
An approach to abductive inference developed in the TACITUS project has resulted in a dramatic simplification of how the problem of interpreting texts is conceptualized. Its use in solving the local pragmatics problems of reference, compound nominals, syntactic ambiguity, and metonymy is described

Incorporating non-local information into information extraction systems by Gibbs sampling

by Jenny Rose Finkel, Trond Grenager, Christopher Manning - IN ACL , 2005
"... Most current statistical natural language processing models use only local features so as to permit dynamic programming in inference, but this makes them unable to fully account for the long distance structure that is prevalent in language use. We show how to solve this dilemma with Gibbs sampling, ..."
Abstract - Cited by 730 (25 self) - Add to MetaCart
Most current statistical natural language processing models use only local features so as to permit dynamic programming in inference, but this makes them unable to fully account for the long distance structure that is prevalent in language use. We show how to solve this dilemma with Gibbs sampling

Points-to Analysis in Almost Linear Time

by Bjarne Steensgaard , 1996
"... We present an interprocedural flow-insensitive points-to analysis based on type inference methods with an almost linear time cost complexity. To our knowledge, this is the asymptotically fastest non-trivial interprocedural points-to analysis algorithm yet described. The algorithm is based on a non-s ..."
Abstract - Cited by 595 (3 self) - Add to MetaCart
We present an interprocedural flow-insensitive points-to analysis based on type inference methods with an almost linear time cost complexity. To our knowledge, this is the asymptotically fastest non-trivial interprocedural points-to analysis algorithm yet described. The algorithm is based on a non

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
Results 1 - 10 of 27,496