Jaynes, E. T. 1979. Where do we stand on maximum entropy? In Levine, R. D., and Tribus, M., eds., The Maximum Entropy Formalism. Cambridge, MA.: MIT Press. 15--118. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
First 50 documents Next 50
Evolutionary Algorithms in Noisy Environments: Theoretical Issues.. - Beyer (1998) (6 citations) (Correct)
.... Here, f(r) is (usually) a monotonic function with r : ky Gamma yk 0, and is a Gaussian noise term with zero mean and standard deviation oe = N (0; oe (r) 2) Assuming a normal noise distribution may be regarded as an approximation of reality based on the maximum entropy principle [19]. Furthermore, it will simplify the derviations considerably. The pdf (probability density function) of the noise reads p( 3) Note, the noise strength oe can be a function of r, allowing for the modeling of relative measuring errors. We will evaluate the performance of sGAs ....
E. T. Jaynes. Where Do We Stand on Maximum Entropy? In R.D. Levine and M. Tribus, editors, The Maximum Entropy Formalism, pages 15--118, 1979.
Generating Random Solutions from a Constraint Satisfaction.. - Larkin (Correct)
....of problems. It is also possible to introduce additional approximation algorithms with further variations of the mini bucket technique, as in Iterative Join Graph propagation [5] It would also be interesting to nd the constraint satisfying probability distribution that has maximum entropy [9], rather than choosing one arbitrarily. ....
E. T. Jaynes. Where do we stand on maximum entropy? In The Maximum Entropy Formalism. M. I. T. Press, 1979.
Bayesian Probability - Bruyninckx (2002) (Correct)
....satisfactorily: Je#reys non informative prior distribution works only for location parameters, such as the mean value of a parameter. For other properties, such as e.g. the standard deviation, other ignorance prior distributions are needed. Jaynes s approaches to find ignorance priors are [15, 16, 17, 18]: 1. Invariance under transformations. If the only thing one knows about the system is a model or an hypothesis, this ignorance should not change if the mathematical representation of the model is transformed into an equivalent representation. For example, a uniform distribution on x does not ....
E. T. Jaynes. Where do we stand on Maximum Entropy? In R. D. Levine and M. Tribus, editors, The maximum entropy formalism, pages 15--118. MIT Press, 1978. Reprinted in [29, p. 211--314].
A Parametric Texture Model based on Joint Statistics of.. - Portilla, Simoncelli (2000) (39 citations) (Correct)
....it successfully for synthesis. The maximum entropy density is optimal in the sense that it does not introduce any constraints on the RF beyond those of equation (3) The form of the maximum entropy density may be derived by solving the constrained optimization problem using Lagrange multipliers [34]: P ( x) k e k k ( x) 4) where x 2 IR corresponds to a (vectorized) image, and the k are the Lagrange multipliers. The values of the multipliers must be chosen such that the density satis es the constraints given in equation (3) But the multipliers are generally a ....
E T Jaynes. Where do we stand on maximum entropy? In R. D. Levine and M. Tribus, editors, The Maximal Entropy Formalism. MIT Press, Cambridge, MA, 1978.
A Probabilistic Approach to Lexical Semantic Knowledge Acquisition.. - Li (1998) (Correct)
....et al. s method defines, for example, a feature as follows f i = 1 (p, n 2 ) is attached to n 1 in ( ice cream, with, chocolate) 0 otherwise. It then incrementally selects features, and e#ciently estimates the conditional distribution by using the Maximum Entropy Estimation technique (see (Jaynes, 1978; Darroch and Ratcli#, 1972; Berger, Pietra, and Pietra, 1996) Another method of the quadruple approach is to employ transformation based error driven learning (Brill, 1995) as proposed in (Brill and Resnik, 1994) This method learns and uses IF THEN type rules, where the IF parts represent ....
Jaynes, E. T. 1978. Where do we stand on maximum entropy? In R. D. Levine and M. Tribus, editors, The Maximum Entropy Formalism. MIT Press.
How To Analyse Evolutionary Algorithms - Beyer, al. (2002) (1 citation) (Correct)
.... by expansions of a Gaussian (also used in ES theory, see Beyer [62, 63] The peculiarity of this approach is, however, that the underlying microscopic description level is bypassed using inference methods gleaned from statistical mechanics, especially the maximum entropy principle (Jaynes [64]) For an introduction into this interesting method as well as further references, the reader is referred to PrugelBennett and Rogers [65] and Shapiro [66] Reviewing the history one may conclude that the theory on evolutionary algorithms has tried to obtain too general statements or too precise ....
E. T. Jaynes. Where do we stand on maximum entropy? In R.D. Levine and M. Tribus, editors, The Maximum Entropy Formalism, pages 15--118, Cambridge, MA, 1979. MIT Press.
Yet Another Analysis of Dice Problems - Mohammad-Djafari (Correct)
....will answer a few questions of Tony and other participants of the workshop on the situations where we can use Maximum Entropy or Bayesian approaches or even the cases where we can actually use both of them. INTRODUCTION Dice problems have been analyzed many times (See mainly Ed. Jaynes papers [1, 2, 3, 4] and also [5, 6, 7, 8, 9] but it seems that still many questions are open. In this note, I will try to answer some of them. Before starting, we need to set up precise notations and describe precisely the context. Let consider an imaginary die with faces ( is the ordinary die) where on ....
E. T. Jaynes, "Where do we stand on maximum entropy ?," in The Maximum Entropy Formalism, R. D. Levine and M. Tribus, Eds. M.I.T. Press, Cambridge (MA), 1978.
Connecting Lexicographic with Maximum Entropy Entailment - Bourne, Parsons (2000) (Correct)
....compute MINF(r i ) c) Select r j with minimal MINF(r i ) d) If MINF(r j ) INF let (r j ) 0 else let (r j ) s j MINV(r j ) Gamma MINF(r j ) 3] Assign ranks to models using equation (2) 4] Check constraints (1) to verify this is an me valid ranking. Fig. 3. The me algorithm [5]. If one has to select a PD from all possible ones, choosing one other than that which has maximum entropy means making additional assumptions or implicitly assuming extra constraints. It would be useful therefore to be able to compare systems of default reasoning with the answers obtained from ....
....represent rational consequence relations [3] The me rankings differ because the different strengths change the default information being encoded. However, the me ranking corresponding to any given set of strengths represents the least biased estimate of the underlying probability distribution [5]. In contrast, the lex ordering is unique and fixed for a given set of defaults [7] It follows that the lex ordering implies some additional assumptions are being made about what default information represents and it is reasonable to ask what these might be. By showing that the lex ordering can ....
[Article contains additional citation context not shown here]
E. Jaynes. Where do we stand on maximum entropy? In R. Levine and M. Tribus, editors, The Maximum Entropy Formalism, pages 15--118, Cambridge, MA, 1979. MIT Press.
Maximum Entropy Probabilistic Logic - Mark Paskin Computer (Correct)
No context found.
Jaynes, E. T. 1979. Where do we stand on maximum entropy? In Levine, R. D., and Tribus, M., eds., The Maximum Entropy Formalism. Cambridge, MA.: MIT Press. 15--118.
The Factorized Distribution Algorithm and the Minimum.. - Mühlenbein, Höns (Correct)
No context found.
E. T. Jaynes. Where do we stand on maximum entropy? In R. D. Levine and M. Tribus, editors, The Maximum Entropy Formalism. MIT Press, Cambridge, 1978.
Sequence Modeling with Mixtures of Conditional Maximum.. - Dmitry Pavlov Yahoo (2003) (Correct)
No context found.
E. T. Jaynes. Where do we stand on maximum entropy? In The Maximum Entropy Formalism, pages 15---118, Cambridge MA, 1979. MIT Press.
Intelligent Machines in the Twenty-First Century: Foundations of.. - Knuth (2003) (Correct)
No context found.
Jaynes, E. T. 1979 Where do we stand on maximum entropy? In The maximum entropy formalism (ed. R. D. Levine & M. Tribus), pp. 15-118. Cambridge, MA: MIT Press.
Deriving Laws from Ordering Relations - Knuth (Correct)
No context found.
Jaynes, E. T., "Where do we stand on maximum entropy," in The Maximum Entropy Formalism, edited by R. D. Levine and M. Tribus, The MIT Press, Cambridge, 1979, pp. 15--118.
Lattice Duality: The Origin of Probability and Entropy - Knuth (2004) (Correct)
No context found.
Jaynes E.T. Where do we stand on maximum entropy? In The Maximum Entropy Formalism (eds. R. D. Levine & M. Tribus), pp. 15--118, Cambridge:MIT Press, 1979.
Measuring Questions: Relevance and its Relation to Entropy - Knuth (2004) (Correct)
No context found.
Jaynes, E. T., "Where do we stand on maximum entropy," in The Maximum Entropy Formalism, edited by R. D. Levine and M. Tribus, The MIT Press, Cambridge, 1979, pp. 15--118.
An Information Theoretic Point of View to MIMO Channel Modelling - Debbah (2003) (Correct)
No context found.
E. T. Jaynes, "Where Do We Stand on Maximum Entropy?," in The Maximum Entropy Formalism,R. D. Levine and M. Tribus (eds.), M. I. T. Press, Cambridge, MA,, p. 15, 1978.
Generating Solutions to Constraint Satisfaction Problems with.. - Larkin (2002) (Correct)
No context found.
E. T. Jaynes. Where do we stand on maximum entropy? In The Maximum Entropy Formalism. M. I. T. Press, 1979.
Final Report on Channel Models - Debbah, al. (2003) (Correct)
No context found.
E. T. Jaynes, "Where do we stand on maximum entropy?," in The Maximum Entropy Formalism,R. D. Levine and M. Tribus (eds.), M. I. T. Press, Cambridge, MA,, p. 15, 1978.
MIMO Channel Modelling and the Principle of Maximum Entropy - Debbah, Müller (2004) (Correct)
No context found.
E. T. Jaynes, "Where Do We Stand on Maximum Entropy?," in The Maximum Entropy Formalism,R. D. Levine and M. Tribus (eds.), M. I. T. Press, Cambridge, MA,, p. 15, 1978.
MIMO Channel Modelling and the Principle of Maximum Entropy.. - Debbah, Müller (2003) (Correct)
No context found.
E. T. Jaynes, "Where Do We Stand on Maximum Entropy?," in The Maximum Entropy Formalism,R. D. Levine and M. Tribus (eds.), M. I. T. Press, Cambridge, MA,, p. 15, 1978.
Generating Solutions to Constraint Satisfaction - Problems With Arbitrary (Correct)
No context found.
E. T. Jaynes. Where do we stand on maximum entropy? In The Maximum Entropy Formalism. M. I. T. Press, 1979.
Asymptotic Conditional Probabilities: The Unary Case - Grove, Halpern, Koller (1993) (2 citations) (Correct)
No context found.
E. T. Jaynes, Where do we stand on maximum entropy?, in The MaximumEntropyFormalism, R. D. Levine and M. Tribus, eds., MIT Press, Cambridge, Mass., 1978, pp. 15--118.
Asymptotic Conditional Probabilities: The Non-unary Case - Adam Grove Nec (1993) (2 citations) (Correct)
No context found.
E. T. Jaynes. Where do we stand on maximum entropy? In R. D. Levine and M. Tribus, editors, The Maximum Entropy Formalism, pages 15--118. MIT Press, Cambridge, Mass., 1978.
Frames: a Maximum Entropy Statistical Estimate of.. - Rebollo-Neira.. (1997) (Correct)
No context found.
E. T. Jaynes, " Where do we Stand Maximum Entropy?," in The Maximum Entropy Formalism, Ed. R. Levine and M. Tribus ( MIT, Boston, 1979).
Generating Degrees of Belief from Statistical.. - Bacchus, Grove.. (1993) (Correct)
No context found.
E. T. Jaynes. Where do we stand on maximum entropy? In R. D. Levine and M. Tribus, editors, The Maximum Entropy Formalism, pages 15--118. MIT Press, Cambridge, MA, 1978.
First 50 documents Next 50
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC