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Self-discrepancy: A theory relating self and affect

by E. Tory Higgins - PSYCHOLOGICAL REVIEW , 1987
"... This article presents a theory of how different types of discrepancies between self-state representations are related to different kinds of emotional vulnerabilities. One domain of the self (actual; ideal; ought) and one standpoint on the self (own; significant other) constitute each type of self-st ..."
Abstract - Cited by 599 (7 self) - Add to MetaCart
with agitation-related emotions (e.g., fear, threat, restlessness). Differences in both the relative magnitude and the accessibility of individu-als ' available types of self-discrepancies are predicted to be related to differences in the kinds of discomfort people are likely to experience. Correlational

Toward an instance theory of automatization

by Gordon D. Logan - Psychological Review , 1988
"... This article presents a theory in which automatization is construed as the acquisition of a domain-specific knowledge base, formed of separate representations, instances, of each exposure to the task. Processing is considered automatic if it relies on retrieval of stored instances, which will occur ..."
Abstract - Cited by 647 (38 self) - Add to MetaCart
This article presents a theory in which automatization is construed as the acquisition of a domain-specific knowledge base, formed of separate representations, instances, of each exposure to the task. Processing is considered automatic if it relies on retrieval of stored instances, which will occur

A theory of social comparison processes,”

by Leon Festinger - Human Relations, , 1954
"... In this paper we shall present a further development of a previously published theory concerning opinion influence processes in social groups (7). This further development has enabled us to extend the theory to deal with other areas, in addition to opinion formation, in which social comparison is i ..."
Abstract - Cited by 1318 (0 self) - Add to MetaCart
, specifically designed to test predictions from this extension of the theory, have now been completed Hypothesis I: There exists, in the human organism, a drive to evaluate his opinions and his abilities. While opinions and abilities may, at first glance, seem to be quite different things, there is a close

From Data Mining to Knowledge Discovery in Databases.

by Usama Fayyad , Gregory Piatetsky-Shapiro , Padhraic Smyth - AI Magazine, , 1996
"... ■ Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. What is all the excitement about? This article provides an overview of this emerging field, clarifying how data mining and knowledge discovery in database ..."
Abstract - Cited by 538 (0 self) - Add to MetaCart
predictive model for estimating the value of future cases). At the core of the process is the application of specific data-mining methods for pattern discovery and extraction. 1 This article begins by discussing the historical context of KDD and data mining and their intersection with other related fields. A

Motivation through the Design of Work: Test of a Theory. Organizational Behavior and Human Performance,

by ] Richard Hackman , Grec R Oldham , 1976
"... A model is proposed that specifies the conditions under which individuals will become internally motivated to perform effectively on their jobs. The model focuses on the interaction among three classes of variables: (a) the psychological states of employees that must be present for internally motiv ..."
Abstract - Cited by 622 (2 self) - Add to MetaCart
of the theorizing (cf. Porter, Lawler, & Hackman, 1975, Chap. 10). We then propose and report a test of a theory of work redesign that focuses specifically on how the characteristics of jobs and the characteristics of people interact to determine when an "enriched" job will lead to beneficial outcomes

A framework for learning predictive structures from multiple tasks and unlabeled data

by Rie Kubota Ando, Tong Zhang - JOURNAL OF MACHINE LEARNING RESEARCH , 2005
"... One of the most important issues in machine learning is whether one can improve the performance of a supervised learning algorithm by including unlabeled data. Methods that use both labeled and unlabeled data are generally referred to as semi-supervised learning. Although a number of such methods ar ..."
Abstract - Cited by 443 (3 self) - Add to MetaCart
are proposed, at the current stage, we still don’t have a complete understanding of their effectiveness. This paper investigates a closely related problem, which leads to a novel approach to semi-supervised learning. Specifically we consider learning predictive structures on hypothesis spaces (that is, what

Active Perception

by Ruzena Bajcsy , 1988
"... Active Perception (Active Vision specifically) is defined as a study of Modeling and Control strategies for perception. By modeling we mean models of sensors, processing modules and their interac-tion. We distinguish local models from global models by their extent of application in space and time. T ..."
Abstract - Cited by 431 (12 self) - Add to MetaCart
Active Perception (Active Vision specifically) is defined as a study of Modeling and Control strategies for perception. By modeling we mean models of sensors, processing modules and their interac-tion. We distinguish local models from global models by their extent of application in space and time

Computational Models of Sensorimotor Integration

by Zoubin Ghahramani , Daniel M. Wolpert, Michael I. Jordan - SCIENCE , 1997
"... The sensorimotor integration system can be viewed as an observer attempting to estimate its own state and the state of the environment by integrating multiple sources of information. We describe a computational framework capturing this notion, and some specific models of integration and adaptati ..."
Abstract - Cited by 424 (12 self) - Add to MetaCart
The sensorimotor integration system can be viewed as an observer attempting to estimate its own state and the state of the environment by integrating multiple sources of information. We describe a computational framework capturing this notion, and some specific models of integration

Multiple Paired Forward and Inverse Models for Motor Control

by D.M. Wolpert, M. Kawato , 1998
"... Humans demonstrate a remarkable ability to generate accurate and appropriate motor behavior under many different and often uncertain environmental conditions. In this paper, we propose a modular approach to such motor learning and control. We review the behavioral evidence and benefits of modularity ..."
Abstract - Cited by 394 (16 self) - Add to MetaCart
the contribution of each inverse model's output to the final motor command. This architecture can simultaneously learn the multiple inverse models necessary for control as well as how to select the inverse models appropriate for a given environment. Finally, we describe specific predictions of the model

The Determinants of Credit Spread Changes.

by Pierre Collin-Dufresne , Robert S Goldstein , J Spencer Martin , Gurdip Bakshi , Greg Bauer , Dave Brown , Francesca Carrieri , Peter Christoffersen , Susan Christoffersen , Greg Duffee , Darrell Duffie , Vihang Errunza , Gifford Fong , Mike Gallmeyer , Laurent Gauthier , Rick Green , John Griffin , Jean Helwege , Kris Jacobs , Chris Jones , Andrew Karolyi , Dilip Madan , David Mauer , Erwan Morellec , Federico Nardari , N R Prabhala , Tony Sanders , Sergei Sarkissian , Bill Schwert , Ken Singleton , Chester Spatt , René Stulz - Journal of Finance , 2001
"... ABSTRACT Using dealer's quotes and transactions prices on straight industrial bonds, we investigate the determinants of credit spread changes. Variables that should in theory determine credit spread changes have rather limited explanatory power. Further, the residuals from this regression are ..."
Abstract - Cited by 422 (2 self) - Add to MetaCart
are highly cross-correlated, and principal components analysis implies that they are mostly driven by a single common factor. An important implication of this finding is that if any explanatory variables have been omitted, they are likely not firm-specific. We therefore re-run the regression, but 1 this time
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