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Regret and Jeffreys Integrals in Exp. Families
"... Let fP j 2 can g be a 1dimensional exponential family given in a canonical parameterization, dP dQ 1 Z ( ) e x; (1) where Z is the partition function Z ( ) = R exp ( x) dQx, and can: = f j Z ( ) < 1g is the canonical parameter space. We let sup = supf j 2 can g, and inf likewise. The elements o ..."
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of the exponential family are also parametrized by their mean value. We write for the mean value corresponding to the canonical parameter and for the canonical parameter corresponding to the mean value: For any x the maximum likelihood distribution is P x: The Shtarkov integral S is de ned as
Finiteness of Redundancy, Regret, Shtarkov Sums, and Jeffreys Integrals in Exponential Families
, 2009
"... The normalized maximum likelihood (NML) distribution plays a fundamental role in the MDL approach to statistical inference. It is only defined for statistical families with a finite Shtarkov sum. Here we characterize, for 1dimensional exponential families, when the Shtarkov sum is finite. This tur ..."
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. This turns out to be the case if and only if the minimax redundancy is finite, thus extending the reach of our results beyond the individualsequence setting. In practice, the NML/Shtarkov distribution is often approximated by the Bayesian marginal distribution based on Jeffreys' prior. One serious
JEFFREY FRANKEL
, 2014
"... We propose a framework that, building on the pledges made by governments after the Copenhagen Accord of 2009, could be used to assign allocations of emissions of greenhouse gases (GHGs), across all countries, one budget period at a time, as envisioned at the 2011 negotiations in Durban. Under this t ..."
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numerical formula that each country is likely to view as fair. We use a state of the art integrated assessment model to project economic and environmental effects of the computed emission targets.
Simulating Normalized Constants: From Importance Sampling to Bridge Sampling to Path Sampling
, 1998
"... Computing (ratios of) normalizing constants of probability models is a fundamental computational problem for many statistical and scientific studies. Monte Carlo simulation is an effective technique, especially with complex and highdimensional models. This paper aims to bring to the attention of ..."
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Cited by 233 (5 self)
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efficiency to thermodynamic integration, and the search of optimal paths turns out to have close connections with the Jeffreys prior density and the Rao and Hellinger distances between two densities. We provide an informative theoretical example as well as two empirical examples (involving 17 to 70
From the SelectedWorks of Jeffrey S. Morris
, 2013
"... Bayesian methods for expressionbased integration ..."
, Breck Baldwin, Jeffrey C. Reynar and B. Srinivas
 Proceedings of the International Workshop on Lexically Driven Information Extraction
, 1996
"... We present Mother of Perl, a pattern description language developed for use in information extraction. Patterns are described in mop by lefttoright enumeration of components, with each component specified at the appropriate level of descriptive granularity. The patterns are compiled into Perl scr ..."
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scripts, which perform backtracking search on the input text. mop also allows for rapid integration of a variety of analytical modules, such as partofspeech taggers and parsers. 1 Introduction Information extraction (IE) is the task of processing large volumes of texts in order to extract
1BAYESIAN ESTIMATION OF A BIVARIATE COPULA USING THE JEFFREYS PRIOR
"... Abstract: A bivariate distribution with continuous margins can be uniquely decomposed via a copula and its marginal distributions. We consider the problem of estimating the copula function and adopt a Bayesian approach. On the space of copula functions, we construct a finite dimensional approximati ..."
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approximation subspace which is parametrized by a doubly stochastic matrix. A major problem here is the selection of a prior distribution on the space of doubly stochastic matrices also known as the Birkhoff polytope. The main contributions of this paper are the derivation of a simple formula for the Jeffreys
Cultural Trauma? On the Most Recent Turn in Jeffrey Alexander’s Cultural Sociology
"... – the most fervent proponent of a neoParsonian approach in social theory. More than Münch, however, Alexander has distanced himself from Parsons ’ own understanding of culture and attempted to integrate recent developments of cultural theory and the potential of the lateDurkheimian writings into h ..."
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Cited by 3 (0 self)
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– the most fervent proponent of a neoParsonian approach in social theory. More than Münch, however, Alexander has distanced himself from Parsons ’ own understanding of culture and attempted to integrate recent developments of cultural theory and the potential of the lateDurkheimian writings
On graduation from fiscal procyclicality ∗ Jeffrey A. Frankel Harvard University and NBER
, 2012
"... In the past, industrial countries have tended to pursue countercyclical or, at worst, acyclical fiscal policy. In sharp contrast, emerging and developing countries have followed procyclical fiscal policy, thus exacerbating the underlying business cycle. We show that, over the last decade, about a th ..."
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third of the developing world has been able to escape the procyclicality trap and actually become countercyclical. In line with existing literature, we confirm the role of increased financial integration and lower output volatility in reducing overall procyclicality. In this paper, however, we focus
Jeffrey Gray’s Consciousness: Creeping up on the Hard Problem will be enjoyed by
"... everyone interested in consciousness. Gray, a neuropsychologist, eloquently summarizes significant experimental results on consciousness and, more importantly, explains both how these results interrelate and how they constrain potential theories of consciousness. He also uses these results to build ..."
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problems requires explaining how we execute certain functions; e.g. how we extract information from sensory stimuli, how we integrate that information, and how we report our thoughts. Solving the Hard Problem requires explaining why there is something it is like for us to execute those functions (or
Results 1  10
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