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On Maximum Entropy and Inference

Luigi Gresele, Matteo Marsili
2017 Entropy  
Maximum Entropy is a powerful concept that entails a sharp separation between relevant and irrelevant variables.  ...  It is typically invoked in inference, once an assumption is made on what the relevant variables are, in order to estimate a model from data, that affords predictions on all other (dependent) variables.  ...  Lee and William Bialek for sharing the data of [8] .  ... 
doi:10.3390/e19120642 fatcat:5m2r4qu4tvhsndermujeqnt7xe

Maximum Entropy Distributions Inferred from Option Portfolios on an Asset [article]

C. Neri and L. Schneider (EMLYON Business School, Lyon, France)
2011 arXiv   pre-print
We obtain the maximum entropy distribution for an asset from call and digital option prices.  ...  Finally, we apply our approach to options on the S&P 500 index.  ...  The Maximum Entropy Distribution Using Calls and Digitals Maximum Entropy Distribution We are given a fixed maturity T , strictly increasing strikes K 0 = 0, K 1 , ..., K n , K n+1 = ∞, and undiscounted  ... 
arXiv:0903.4542v3 fatcat:rouz2b7vofa2tmt5jeqtpksxym

Maximum-Entropy Inference and Inverse Continuity of the Numerical Range

Stephan Weis
2016 Reports on mathematical physics  
We study the continuity of the maximum-entropy inference map for two observables in finite dimensions.  ...  It shows also that the continuity of the MaxEnt inference method is independent of the prior state.  ...  Discontinuity points of the maximum-entropy inference exist on the boundary of the set of expected values while the analogous maximum-entropy inference of probability distributions is continuous.  ... 
doi:10.1016/s0034-4877(16)30022-2 fatcat:p4zpacvtu5hufdvnenej4spiam

On The Relationship between Bayesian and Maximum Entropy Inference

Peter Cheeseman
2004 AIP Conference Proceedings  
We investigate Bayesian and Maximum Entropy methods for doing inference under uncertainty.  ...  We generalize the classic method of maximum entropy inference to allow for uncertainty in the constraint values.  ...  Contingency pdf = probability density function.On The Relationship between Bayesian and Maximum Entropy InferenceSeptember 21, 2004 On The Relationship between Bayesian and Maximum Entropy InferenceSeptember  ... 
doi:10.1063/1.1835243 fatcat:lkaz4aj2x5gkbaehm6qkonprhu

Network Inference and Maximum Entropy Estimation on Information Diagrams

Elliot A. Martin, Jaroslav Hlinka, Alexander Meinke, Filip Děchtěrenko, Jaroslav Tintěra, Isaura Oliver, Jörn Davidsen
2017 Scientific Reports  
Maximum entropy estimation is of broad interest for inferring properties of systems across many disciplines.  ...  Using a recently introduced technique for estimating the maximum entropy of a set of random discrete variables when conditioning on bivariate mutual informations and univariate entropies, we show how this  ...  Acknowledgements This project was financially supported by NSERC (EM, IO and JD) and by the Czech Science Foundation project GA13-23940S and the Czech Health Research Council project NV15-29835A and project  ... 
doi:10.1038/s41598-017-06208-w pmid:28765522 pmcid:PMC5539257 fatcat:zwndcc3e7vcpvcl7sfsitappsi

On the `fake' inferred entanglement associated with the maximum entropy inference of quantum states

J Batle, M Casas, A R Plastino, A Plastino
2001 Journal of Physics A: Mathematical and General  
The fake entanglement generated by the maximum entropy principle is also studied quantitatively by comparing the entanglement of formation of the inferred state with that of the original one.  ...  The inference of entangled quantum states by recourse to the maximum entropy principle is considered in connection with the recently pointed out problem of fake inferred entanglement [R.  ...  ACKNOWLEDGMENTS This work was partially supported by the AECI Scientific Cooperation Program, by the DGES grants PB98-0124 and SB97-26373862 (Spain), and by CONICET (Argentine Agency).  ... 
doi:10.1088/0305-4470/34/33/309 fatcat:kp4x2dqvubclvfr5dkz6xbviii

On Bayesian Inference, Maximum Entropy and Support Vector Machines Methods

Mihai Costache, Marie Liénou, Mihai Datcu
2006 AIP Conference Proceedings  
The analysis of discrimination, feature and model selection conduct to the discussion of the relationships between Support Vector Machine (SVM), Bayesian and Maximum Entropy (MaxEnt) formalisms.  ...  In addition, the similarities with the kernels based on Kullback-Leibler divergence can be deduced, thus returning with MaxEnt similarity.  ...  On Bayesian Inference, Maximum Entropy and Support Vector Machines Methods19th September 20062 On Bayesian Inference, Maximum Entropy and Support Vector Machines Methods19th September 20069  ... 
doi:10.1063/1.2423259 fatcat:ker4jxfh3jgrznzejzyqkirny4

Inferences on the Higgs Boson and Axion Masses through a Maximum Entropy Principle [article]

Alexandre Alves, Alex G. Dias, Roberto da Silva
2017 arXiv   pre-print
In this work we review two applications of MEP: one giving a precise inference of the Higgs boson mass value; and the other one allowing to infer the mass of the axion.  ...  The Maximum Entropy Principle (MEP) is a method that can be used to infer the value of an unknown quantity in a set of probability functions.  ...  It is shown in green on Fig. 3 the maximum points of the entropy S(m A |m 1 , r ν ).  ... 
arXiv:1711.00417v1 fatcat:6hkyequ4u5cwnow5i2cqayrx54

Legendre Transformation and Information Geometry for the Maximum Entropy Theory of Ecology

Pedro Pessoa
2021 The 40th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering   unpublished
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// 4.0/).  ...  The work of Harte and collaborators [23] [24] [25] [26] [27] presents what is known as the maximum entropy theory of ecology (METE).  ...  Introduction The method of maximum entropy (MaxEnt) is usually associated with Jaynes' work [1] [2] [3] connecting statistical physics and the information entropy proposed by Shannon [4] although its  ... 
doi:10.3390/psf2021003001 fatcat:yzftifqanfaufprziupuwj4itu

Inferring semantic roles using sub-categorization frames and maximum entropy model

Akshar Bharati, Sriram Venkatapathy, Prashanth Reddy
2005 Proceedings of the Ninth Conference on Computational Natural Language Learning - CONLL '05   unpublished
In this paper, we propose an approach for inferring semantic role using subcategorization frames and maximum entropy model.  ...  The unlabelled mandatory arguments and the optional arguments are labelled directly using the maximum entropy model such that their labels are not one among the frame elements of the sub-categorization  ...  Sushama Bendre and Dr. Dipti Misra Sharma for guiding us in this project. We would like to thank Szu-ting for giving some valuable advice.  ... 
doi:10.3115/1706543.1706572 fatcat:rc6nxxlid5cudaavtrmfxbvude

Uncertain Reasoning using Maximum Entropy Inference [chapter]

Daniel Hunter
1986 Machine Intelligence and Pattern Recognition  
On this view of maximum entropy inference, maximum relative entropy, or cross-entropy, is the basic notion, and what is known simply as "maximum entropy" is maximum relative entropy with re spect to a  ...  In this sense maximum entropy inference addresses only the dynamic prob lem and not the static one.  ... 
doi:10.1016/b978-0-444-70058-2.50019-x fatcat:g4733hkbzzbm5mr7sahsgcdyba

The maximum entropy method for analyzing retrieval measures

Javed A. Aslam, Emine Yilmaz, Virgiliu Pavlu
2005 Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '05  
We present a model, based on the maximum entropy method, for analyzing various measures of retrieval performance such as average precision, R-precision, and precision-at-cutoffs.  ...  Our methodology treats the value of such a measure as a constraint on the distribution of relevant documents in an unknown list, and the maximum entropy distribution can be determined subject to these  ...  More specifically, we develop a framework based on the maximum entropy method which allows one to infer the most "reasonable" model for the sequence of relevant and non-relevant documents in a list given  ... 
doi:10.1145/1076034.1076042 dblp:conf/sigir/AslamYP05 fatcat:xutchgazcbbnnbc4m4k76elaui

Reply to "Comment on 'Inference with minimal Gibbs free energy in information field theory' "

Torsten A. Enßlin, Cornelius Weig
2012 Physical Review E  
Furthermore, a distinction is made here between maximum entropy, the maximum entropy principle, and the so-called maximum entropy method in imaging, hopefully clarifying further the second issue of their  ...  We endorse the comment on our recent paper [Enßlin and Weig, Phys. Rev. E 82, 051112 (2010)] by Iatsenko, Stefanovska and McClintock [Phys. Rev.  ...  Stefanovska and P. V. E. McClintock for the collegial way they discussed their comments with us.  ... 
doi:10.1103/physreve.85.033102 fatcat:ehy64bpwwvawzko3prhjgkesai

Discontinuities in the Maximum-Entropy Inference [article]

Stephan Weis
2013 arXiv   pre-print
We point out the existence of discontinuities in this inference method. This is a pure quantum phenomenon since the maximum-entropy inference is continuous for mutually commuting observables.  ...  We revisit the maximum-entropy inference of the state of a finite-level quantum system under linear constraints. The constraints are specified by the expected values of a set of fixed observables.  ...  ACKNOWLEDGMENTS We would like to thank Arleta Szkoła and Michael Nussbaum for an interesting discussion about maximizing entropies.  ... 
arXiv:1308.6126v1 fatcat:s67w3sbcfjgtzoouqwrjsaadke

Maximum Entropy in Drug Discovery

Chih-Yuan Tseng, Jack Tuszynski
2014 Entropy  
Finally, we discuss a promising new direction in drug discovery that is likely to hinge on the ways of utilizing maximum entropy.  ...  In this article, we provide an overview of the current strategies and point out where and how the method of maximum entropy has been introduced in this area.  ...  Jack Tuszynski acknowledges funding for this research from Natural Science and Engineering Research Council of Canada (NSERC).  ... 
doi:10.3390/e16073754 fatcat:mx5ynkqi4bd63j2i7jgvljmrna
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