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132,899
L.: Additioninvariant FO and regularity
 In: Proc. of LICS (2010
"... We consider formulas which, in addition to the symbols in the vocabulary, may use two designated symbols≺and+ that must be interpreted as a linear order and its associated addition. Such a formula is called additioninvariant if, for each fixed interpretation of the initial vocabulary, its result is ..."
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Cited by 5 (3 self)
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is independent of the particular interpretation of ≺ and +. This paper studies the expressive power of additioninvariant firstorder logic, +invFO, on the class of finite strings. Our first main result gives a characterization of the regular languages definable in +invFO: we show that these are exactly
Regular tree languages, cardinality predicates, and additioninvariant FO
"... This paper considers the logic FOcard, i.e., firstorder logic with cardinality predicates that can specify the size of a structure modulo some number. We study the expressive power of FOcard on the class of languages of ranked, finite, labelled trees with successor relations. Our first main result ..."
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Cited by 1 (1 self)
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interpretation of the unary relations and successor relations, its result is independent of the particular interpretation of < and +. We show that the FOcarddefinable tree languages are exactly the regular tree languages definable in additioninvariant firstorder logic. Our proof techniques involve tools
An Overview of the C++ Programming Language
, 1999
"... This overview of C++ presents the key design, programming, and languagetechnical concepts using examples to give the reader a feel for the language. C++ is a generalpurpose programming language with a bias towards systems programming that supports efficient lowlevel computation, data abstraction, ..."
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Cited by 1766 (15 self)
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This overview of C++ presents the key design, programming, and languagetechnical concepts using examples to give the reader a feel for the language. C++ is a generalpurpose programming language with a bias towards systems programming that supports efficient lowlevel computation, data abstraction
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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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
Orthonormal bases of compactly supported wavelets
, 1993
"... Several variations are given on the construction of orthonormal bases of wavelets with compact support. They have, respectively, more symmetry, more regularity, or more vanishing moments for the scaling function than the examples constructed in Daubechies [Comm. Pure Appl. Math., 41 (1988), pp. 90 ..."
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Cited by 2182 (27 self)
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Several variations are given on the construction of orthonormal bases of wavelets with compact support. They have, respectively, more symmetry, more regularity, or more vanishing moments for the scaling function than the examples constructed in Daubechies [Comm. Pure Appl. Math., 41 (1988), pp
KodairaSpencer theory of gravity and exact results for quantum string amplitudes
 Commun. Math. Phys
, 1994
"... We develop techniques to compute higher loop string amplitudes for twisted N = 2 theories with ĉ = 3 (i.e. the critical case). An important ingredient is the discovery of an anomaly at every genus in decoupling of BRST trivial states, captured to all orders by a master anomaly equation. In a particu ..."
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Cited by 545 (60 self)
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We develop techniques to compute higher loop string amplitudes for twisted N = 2 theories with ĉ = 3 (i.e. the critical case). An important ingredient is the discovery of an anomaly at every genus in decoupling of BRST trivial states, captured to all orders by a master anomaly equation. In a
The pyramid match kernel: Discriminative classification with sets of image features
 IN ICCV
, 2005
"... Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernelbased classification methods can learn complex decision boundaries, but a kernel over unordered set inputs must somehow solve for correspondenc ..."
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Cited by 546 (29 self)
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Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernelbased classification methods can learn complex decision boundaries, but a kernel over unordered set inputs must somehow solve
A Theory of Objects
, 1996
"... Objectoriented languages were invented to provide an intuitive view of data and computation, by drawing an analogy between software and the physical world of objects. The detailed explanation of this intuition, however, turned out to be quite complex; there are still no standard definitions of such ..."
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Cited by 1002 (13 self)
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. Object calculi are based exclusively on objects and methods, not on functions or data structures. They help in classifying and explaining the features of objectoriented languages, and in designing new, more regular languages. They directly inspired my design of Obliq, an objectoriented language
Robust Monte Carlo Localization for Mobile Robots
, 2001
"... Mobile robot localization is the problem of determining a robot's pose from sensor data. This article presents a family of probabilistic localization algorithms known as Monte Carlo Localization (MCL). MCL algorithms represent a robot's belief by a set of weighted hypotheses (samples), whi ..."
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Cited by 826 (88 self)
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to mobile robots equipped with range finders, a kernel density tree is learned that permits fast sampling. Systematic empirical results illustrate the robustness and computational efficiency of the approach.
Locally weighted learning
 ARTIFICIAL INTELLIGENCE REVIEW
, 1997
"... This paper surveys locally weighted learning, a form of lazy learning and memorybased learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias, ass ..."
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Cited by 594 (53 self)
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This paper surveys locally weighted learning, a form of lazy learning and memorybased learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias
Results 1  10
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132,899