Results 1  10
of
524,809
Backwards Forward Induction
, 1993
"... In this paper we isolate a particular refinement of the notion of Nash equilibrium that is characterized by (i) the fact that it provides a unified framework for both backwards and forward induction; and (ii) by the fact that it is mechanically computable. We provide an effective procedure, whose de ..."
Abstract
 Add to MetaCart
In this paper we isolate a particular refinement of the notion of Nash equilibrium that is characterized by (i) the fact that it provides a unified framework for both backwards and forward induction; and (ii) by the fact that it is mechanically computable. We provide an effective procedure, whose
Backwards Forward Induction
, 1994
"... document without permission of its author may be prohibited by law. ..."
Wrapper Induction for Information Extraction
, 1997
"... The Internet presents numerous sources of useful informationtelephone directories, product catalogs, stock quotes, weather forecasts, etc. Recently, many systems have been built that automatically gather and manipulate such information on a user's behalf. However, these resources are usually ..."
Abstract

Cited by 612 (30 self)
 Add to MetaCart
introduce wrapper induction, a technique for automatically constructing wrappers. Our techniques can be described in terms of three main contributions. First, we pose the problem of wrapper construction as one of inductive learn...
A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge
 PSYCHOLOGICAL REVIEW
, 1997
"... How do people know as much as they do with as little information as they get? The problem takes many forms; learning vocabulary from text is an especially dramatic and convenient case for research. A new general theory of acquired similarity and knowledge representation, latent semantic analysis (LS ..."
Abstract

Cited by 1772 (10 self)
 Add to MetaCart
rate to schoolchildren. LSA uses no prior linguistic or perceptual similarity knowledge; it is based solely on a general mathematical learning method that achieves powerful inductive effects by extracting the right number of dimensions (e.g., 300) to represent objects and contexts. Relations to other
Least angle regression
 Ann. Statist
"... 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 1308 (43 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
Factor Graphs and the SumProduct Algorithm
 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 1787 (72 self)
 Add to MetaCart
be derived as specific instances of the sumproduct algorithm, including the forward/backward algorithm, the Viterbi algorithm, the iterative "turbo" decoding algorithm, Pearl's belief propagation algorithm for Bayesian networks, the Kalman filter, and certain fast Fourier transform algorithms.
Testing Game Theory
, 2004
"... Experimentalists frequently claim that human subjects in the laboratory violate gametheoretic predictions. It is here argued that this claim is usually premature. The paper elaborates on this theme by way of raising some conceptual and methodological issues in connection with the very definition of ..."
Abstract

Cited by 996 (15 self)
 Add to MetaCart
of a game and of players ’ preferences, in particular with respect to potential context dependence, interpersonal preference dependence, backward induction and incomplete information.
Irrelevant Features and the Subset Selection Problem
 MACHINE LEARNING: PROCEEDINGS OF THE ELEVENTH INTERNATIONAL
, 1994
"... We address the problem of finding a subset of features that allows a supervised induction algorithm to induce small highaccuracy concepts. We examine notions of relevance and irrelevance, and show that the definitions used in the machine learning literature do not adequately partition the features ..."
Abstract

Cited by 741 (26 self)
 Add to MetaCart
We address the problem of finding a subset of features that allows a supervised induction algorithm to induce small highaccuracy concepts. We examine notions of relevance and irrelevance, and show that the definitions used in the machine learning literature do not adequately partition the features
The Askeyscheme of hypergeometric orthogonal polynomials and its qanalogue
, 1998
"... We list the socalled Askeyscheme of hypergeometric orthogonal polynomials and we give a q analogue of this scheme containing basic hypergeometric orthogonal polynomials. In chapter 1 we give the definition, the orthogonality relation, the three term recurrence relation, the second order di#erent ..."
Abstract

Cited by 580 (6 self)
 Add to MetaCart
#erential or di#erence equation, the forward and backward shift operator, the Rodriguestype formula and generating functions of all classes of orthogonal polynomials in this scheme. In chapter 2 we give the limit relations between di#erent classes of orthogonal polynomials listed in the Askeyscheme. In chapter
Wrappers for Feature Subset Selection
 AIJ SPECIAL ISSUE ON RELEVANCE
, 1997
"... In the feature subset selection problem, a learning algorithm is faced with the problem of selecting a relevant subset of features upon which to focus its attention, while ignoring the rest. To achieve the best possible performance with a particular learning algorithm on a particular training set, a ..."
Abstract

Cited by 1522 (3 self)
 Add to MetaCart
the strengths and weaknesses of the wrapper approach andshow a series of improved designs. We compare the wrapper approach to induction without feature subset selection and to Relief, a filter approach to feature subset selection. Significant improvement in accuracy is achieved for some datasets for the two
Results 1  10
of
524,809