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Context Trees
 In Proceedings of the First Int. Conf. on Automated Reasoning (IJCAR 2001), volume 2083 of LNCS
, 2001
"... Indexing data structures have a crucial impact on the performance of automated theorem provers. Examples are discrimination trees, which are like tries where terms are seen as strings and common prefixes are shared, and substitution trees, where terms keep their tree structure and all common con ..."
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Cited by 6 (1 self)
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contexts can be shared. Here we describe a new indexing data structure, called context trees, where, by means of a limited kind of context variables, also common subterms can be shared, even if they occur below di#erent function symbols. Apart from introducing the concept, we also provide evidence
The ContextTree Weighting Method: Basic Properties
 IEEE Trans. Inform. Theory
, 1995
"... We describe a sequential universal data compression procedure for binary tree sources that performs the "double mixture." Using a context tree, this method weights in an efficient recursive way the coding distributions corresponding to all bounded memory tree sources, and achieves a desira ..."
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Cited by 229 (18 self)
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We describe a sequential universal data compression procedure for binary tree sources that performs the "double mixture." Using a context tree, this method weights in an efficient recursive way the coding distributions corresponding to all bounded memory tree sources, and achieves a
Context Tree Switching
"... This paper describes the Context Tree Switching technique, a modification of Context Tree Weighting for the prediction of binary, stationary, nMarkov sources. By modifying Context Tree Weighting’s recursive weighting scheme, it is possible to mix over a strictly larger class of models without incre ..."
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Cited by 8 (4 self)
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This paper describes the Context Tree Switching technique, a modification of Context Tree Weighting for the prediction of binary, stationary, nMarkov sources. By modifying Context Tree Weighting’s recursive weighting scheme, it is possible to mix over a strictly larger class of models without
Bag Context Tree Grammars
, 2006
"... Bag context is a device for regulated rewriting in tree and string grammars. It represents context that is not part of the developing tree or string, but evolves on its own during a derivation. Motivation for investigating bag context tree languages is provided by showing that the class of bag cont ..."
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Bag context is a device for regulated rewriting in tree and string grammars. It represents context that is not part of the developing tree or string, but evolves on its own during a derivation. Motivation for investigating bag context tree languages is provided by showing that the class of bag
Adaptive Context Tree Weighting
, 2012
"... We describe an adaptive context tree weighting (ACTW) algorithm, as an extension to the standard context tree weighting (CTW) algorithm. Unlike the standard CTW algorithm, which weights all observations equally regardless of the depth, ACTW gives increasing weight to more recent observations, aiming ..."
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Cited by 3 (2 self)
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We describe an adaptive context tree weighting (ACTW) algorithm, as an extension to the standard context tree weighting (CTW) algorithm. Unlike the standard CTW algorithm, which weights all observations equally regardless of the depth, ACTW gives increasing weight to more recent observations
The ContextTree Kernel for Strings
"... We propose a new kernel for strings which borrows ideas and techniques from information theory and data compression. This kernel can be used in combination with any kernel method, in particular Support Vector Machines for string classification, with notable applications in proteomics. By using a Bay ..."
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Bayesian averaging framework with conjugate priors on a class of Markovian models known as probabilistic suffix trees or contexttrees, we compute the value of this kernel in linear time and space while only using the information contained in the spectrum of the considered strings. This is ensured through
The ContextTree Weighting Method: Extensions
 IEEE Transactions on Information Theory
, 1994
"... . First we modify the basic (binary) contexttree weighting method such that the past symbols x 1\GammaD ; x 2\GammaD ; \Delta \Delta \Delta ; x 0 are not needed by the encoder and the decoder. Then we describe how to make the context tree depth D infinite, which results in optimal redundancy behavi ..."
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Cited by 54 (1 self)
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. First we modify the basic (binary) contexttree weighting method such that the past symbols x 1\GammaD ; x 2\GammaD ; \Delta \Delta \Delta ; x 0 are not needed by the encoder and the decoder. Then we describe how to make the context tree depth D infinite, which results in optimal redundancy
Extensions to the Context Tree Weighting Method
"... Abstract We modify the basic context tree weighting method so that past symbols are not needed, and that the context tree depth is infinite. For stationary ergodic sources we now achieve entropy. I. ..."
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Abstract We modify the basic context tree weighting method so that past symbols are not needed, and that the context tree depth is infinite. For stationary ergodic sources we now achieve entropy. I.
Skip Context Tree Switching
"... Context Tree Weighting is a powerful probabilistic sequence prediction technique that efficiently performs Bayesian model averaging over the class of all prediction suffix trees of bounded depth. In this paper we show how to generalize this technique to the class of Kskip prediction suffix trees. ..."
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Cited by 3 (1 self)
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Context Tree Weighting is a powerful probabilistic sequence prediction technique that efficiently performs Bayesian model averaging over the class of all prediction suffix trees of bounded depth. In this paper we show how to generalize this technique to the class of Kskip prediction suffix trees
The Context Trees of Block Sorting Compression
 IN PROCEEDINGS OF THE IEEE DATA COMPRESSION CONFERENCE, SNOWBIRD, UTAH, MARCH 30  APRIL 1
, 1998
"... The BurrowsWheeler transform (BWT)andblock sorting compression are closely related to the context trees of PPM. The usual approach of treating BWT as merely a permutation is not able to fully exploit this relation. We show that ..."
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Cited by 24 (0 self)
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The BurrowsWheeler transform (BWT)andblock sorting compression are closely related to the context trees of PPM. The usual approach of treating BWT as merely a permutation is not able to fully exploit this relation. We show that
Results 1  10
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