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An alphabetfriendly FMindex
 In Proc.SPIRE’04, LNCS 3246
, 2004
"... Abstract. We show that, by combining an existing compression boosting technique with the wavelet tree data structure, we are able to design a variant of the FMindex which scales well with the size of the input alphabet Σ. The size of the new index built on a string T [1, n] is bounded by nHk(T)+O � ..."
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Cited by 49 (18 self)
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Abstract. We show that, by combining an existing compression boosting technique with the wavelet tree data structure, we are able to design a variant of the FMindex which scales well with the size of the input alphabet Σ. The size of the new index built on a string T [1, n] is bounded by n
A Simple AlphabetIndependent FMIndex
 INTERNATIONAL JOURNAL OF FOUNDATIONS OF COMPUTER SCIENCE
"... We design a succinct fulltext index based on the idea of Huffmancompressing the text and then applying the BurrowsWheeler transform over it. The resulting structure can be searched as an FMindex, with the benefit of removing the sharp dependence on the alphabet size, σ, present in that structu ..."
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Cited by 18 (9 self)
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We design a succinct fulltext index based on the idea of Huffmancompressing the text and then applying the BurrowsWheeler transform over it. The resulting structure can be searched as an FMindex, with the benefit of removing the sharp dependence on the alphabet size, σ, present
A SIMPLE ALPHABETINDEPENDENT FMINDEX
 INTERNATIONAL JOURNAL OF FOUNDATIONS OF COMPUTER SCIENCE CFL WORLD SCIENTIFIC PUBLISHING COMPANY
"... ..."
Convex Analysis
, 1970
"... In this book we aim to present, in a unified framework, a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The title Variational Analysis reflects this breadth. For a lo ..."
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Cited by 5350 (67 self)
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long time, ‘variational ’ problems have been identified mostly with the ‘calculus of variations’. In that venerable subject, built around the minimization of integral functionals, constraints were relatively simple and much of the focus was on infinitedimensional function spaces. A major theme
Automatic Musical Genre Classification Of Audio Signals
 IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING
, 2002
"... ... describe music. They are commonly used to structure the increasing amounts of music available in digital form on the Web and are important for music information retrieval. Genre categorization for audio has traditionally been performed manually. A particular musical genre is characterized by sta ..."
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Cited by 811 (32 self)
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by statistical properties related to the instrumentation, rhythmic structure and form of its members. In this work, algorithms for the automatic genre categorization of audio signals are described. More specifically, we propose a set of features for representing texture and instrumentation. In addition a novel
Markov Random Field Models in Computer Vision
, 1994
"... . A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is defined as the maximum a posteriori (MAP) probability estimate of the true labeling. The posterior probability is usually derived from a prior model and a likelihood model. The l ..."
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Cited by 515 (18 self)
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. The latter relates to how data is observed and is problem domain dependent. The former depends on how various prior constraints are expressed. Markov Random Field Models (MRF) theory is a tool to encode contextual constraints into the prior probability. This paper presents a unified approach for MRF modeling
Segmentation of brain MR images through a hidden Markov random field model and the expectationmaximization algorithm
 IEEE TRANSACTIONS ON MEDICAL. IMAGING
, 2001
"... The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogrambased model, the FM has an intrinsic limi ..."
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Cited by 619 (14 self)
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The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogrambased model, the FM has an intrinsic
Greedy Function Approximation: A Gradient Boosting Machine
 Annals of Statistics
, 2000
"... Function approximation is viewed from the perspective of numerical optimization in function space, rather than parameter space. A connection is made between stagewise additive expansions and steepest{descent minimization. A general gradient{descent \boosting" paradigm is developed for additi ..."
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Cited by 951 (12 self)
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Function approximation is viewed from the perspective of numerical optimization in function space, rather than parameter space. A connection is made between stagewise additive expansions and steepest{descent minimization. A general gradient{descent \boosting" paradigm is developed for additive expansions based on any tting criterion. Specic algorithms are presented for least{squares, least{absolute{deviation, and Huber{M loss functions for regression, and multi{class logistic likelihood for classication. Special enhancements are derived for the particular case where the individual additive components are regression trees, and tools for interpreting such \TreeBoost" models are presented. Gradient boosting of regression trees produces competitive, highly robust, interpretable procedures for both regression and classication, especially appropriate for mining less than clean data. Connections between this approach and the boosting methods of Freund and Shapire 1996, and Frie...
Breaking and Fixing the NeedhamSchroeder PublicKey Protocol using FDR
, 1996
"... In this paper we analyse the well known NeedhamSchroeder PublicKey Protocol using FDR, a refinement checker for CSP. We use FDR to discover an attack upon the protocol, which allows an intruder to impersonate another agent. We adapt the protocol, and then use FDR to show that the new protocol is s ..."
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Cited by 716 (13 self)
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In this paper we analyse the well known NeedhamSchroeder PublicKey Protocol using FDR, a refinement checker for CSP. We use FDR to discover an attack upon the protocol, which allows an intruder to impersonate another agent. We adapt the protocol, and then use FDR to show that the new protocol is secure, at least for a small system. Finally we prove a result which tells us that if this small system is secure, then so is a system of arbitrary size. 1 Introduction In a distributed computer system, it is necessary to have some mechanism whereby a pair of agents can be assured of each other's identitythey should become sure that they really are talking to each other, rather than to an intruder impersonating the other agent. This is the role of an authentication protocol. In this paper we use the Failures Divergences Refinement Checker (FDR) [11, 5], a model checker for CSP, to analyse the NeedhamSchroeder PublicKey Authentication Protocol [8]. FDR takes as input two CSP processes, ...
Results 1  10
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