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What is an Infinite Regress Argument?
"... Abstract: I describe the general structure of most infinite regress arguments; introduce some basic vocabulary; present a working hypothesis of the nature and derivation of an infinite regress; apply this working hypothesis to various infinite regress arguments to explain why they fail to entail a ..."
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Abstract: I describe the general structure of most infinite regress arguments; introduce some basic vocabulary; present a working hypothesis of the nature and derivation of an infinite regress; apply this working hypothesis to various infinite regress arguments to explain why they fail to entail
Multiple Head Comparison and Infinite Regress
 WECOL
, 1994
"... this article, I will investigate the semantics of multiple head comparatives and I will show that multiple comparison leads to infinite regress and hence to unacceptability if the two elements introduced by a comparative operator both have a lexical counterpart in the than/asclause. A second compar ..."
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Cited by 3 (3 self)
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this article, I will investigate the semantics of multiple head comparatives and I will show that multiple comparison leads to infinite regress and hence to unacceptability if the two elements introduced by a comparative operator both have a lexical counterpart in the than/asclause. A second
HOW TO DO THINGS WITH AN INFINITE REGRESS ∗
, 2001
"... Scientific method may be viewed either as an argument justifying a conclusion or as a procedure for finding the right answer to some question. Both conceptions occasion the problem of empirical regresses. According to the former approach, it is hard to say what the point of a regress is. According t ..."
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Scientific method may be viewed either as an argument justifying a conclusion or as a procedure for finding the right answer to some question. Both conceptions occasion the problem of empirical regresses. According to the former approach, it is hard to say what the point of a regress is. According
1Infinite Regress with SelfMonitoring Sylvie Kornman
"... To exhibit some autonomy and to be able to treat unexpected situations, a system must have the possiblity to monitor its own behavior: it must be able to assess, analyze and possibly fix its own behavior. A natural extension to this approach is to give the monitoring system the possibility to apply ..."
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upon itself. Some researchers have claimed that this is impossible because it would lead to infinite regress. The claim of this paper is that a sufficient condition for a selfmonitoring system to avoid infinite regress is that its knowledge is sufficient for tackling the monitoring system possible
Infinite Regress: The Blurring of an Architectural GameSpace
"... Architecture and gaming have always been unconnected. Architecture uses a vast array of tools as a means to an end, to show information. The computer gaming industry however, creates virtual worlds for its experiential potential. While this disjunction is explicit I believe that the gaming industry ..."
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Architecture and gaming have always been unconnected. Architecture uses a vast array of tools as a means to an end, to show information. The computer gaming industry however, creates virtual worlds for its experiential potential. While this disjunction is explicit I believe that the gaming industry presents architecture with a medium from which to expand its expression. I explore the redundant nature of the space created when two or more spatial conditions are imbedded/layered within each other. By investigating the separate industries of architecture and gaming, I hope to blur and possibly alleviate the distinctions between the tools that architects and game designers use. With growth in gaming technologies and superior compatibility, architects should have the capacity to work between these two worlds. With such technologies architects or designers can further enhance their design by experiencing their designs through a virtual, immersive and interactive realtime environments. ii Acknowledgements
Infinite Regresses Arising from Prediction/Decision Making in Games ∗† TaiWei Hu‡and Mamoru Kaneko§
, 2013
"... We study infinite regresses arising from prediction/decisionmaking in an person game, taking beliefs and inferences explicitly into account. We adopt epistemic logic GL which is an infinitary extension of KD in order to facilitate our discussions on infinite regresses. As a KDtype epistemic lo ..."
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We study infinite regresses arising from prediction/decisionmaking in an person game, taking beliefs and inferences explicitly into account. We adopt epistemic logic GL which is an infinitary extension of KD in order to facilitate our discussions on infinite regresses. As a KDtype epistemic
Large scale multiple kernel learning
 JOURNAL OF MACHINE LEARNING RESEARCH
, 2006
"... While classical kernelbased learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic combinations of kernel matrices for classification, leading to a convex quadratically constrained quadratic program. We s ..."
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Cited by 340 (20 self)
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show that it can be rewritten as a semiinfinite linear program that can be efficiently solved by recycling the standard SVM implementations. Moreover, we generalize the formulation and our method to a larger class of problems, including regression and oneclass classification. Experimental results
Consistency of the group lasso and multiple kernel learning
 JOURNAL OF MACHINE LEARNING RESEARCH
, 2007
"... We consider the leastsquare regression problem with regularization by a block 1norm, i.e., a sum of Euclidean norms over spaces of dimensions larger than one. This problem, referred to as the group Lasso, extends the usual regularization by the 1norm where all spaces have dimension one, where it ..."
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Cited by 274 (33 self)
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We consider the leastsquare regression problem with regularization by a block 1norm, i.e., a sum of Euclidean norms over spaces of dimensions larger than one. This problem, referred to as the group Lasso, extends the usual regularization by the 1norm where all spaces have dimension one, where
Infinitely imbalanced logistic regression
 The Journal of Machine Learning Research
"... In binary classification problems it is common for the two classes to be imbalanced: one case is very rare compared to the other. In this paper we consider the infinitely imbalanced case where one class has a finite sample size and the other class’s sample size grows without bound. For logistic regr ..."
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Cited by 14 (0 self)
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regression, the infinitely imbalanced case often has a useful solution. Under mild conditions, the intercept diverges as expected, but the rest of the coefficient vector approaches a non trivial and useful limit. That limit can be expressed in terms of exponential tilting and is the minimum of a convex
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
, 2000
"... We examine methods for constructing regression ensembles based on a linear program (LP). The ensemble regression function consists of linear combina tions of base hypotheses generated by some boostingtype base learning algorithm. Unlike the classification case, for regression the set of possible h ..."
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Cited by 23 (8 self)
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hypotheses producible by the base learning algorithm may be infinite. We explicitly tackle the issue of how to define and solve ensemble regression when the hypothesis space is infinite. Our approach is based on a semiinfinite linear program that has an infinite number of constraints and a finite number
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