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Document
Document

... Missing Value Point Estimation Jackknife estimate ...
Chapter 3
Chapter 3

10 Nov
10 Nov

Unit_19__Standard_Deviation_1_of_2
Unit_19__Standard_Deviation_1_of_2

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AIPY: Astronomical Interferometry in Python

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Exploiting Semantics for Big Data Integration

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(1.0 MB PowerPoint)
(1.0 MB PowerPoint)

... Cause the USB device to appear as an addition com port available to the PC. Applications can access the USB device in the same way as it would access a standard COM port. ...
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Weekly Homework Sheet

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Practical 10 - OCaml 2 - Computing Science and Mathematics

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ABSTRACT : Inferences are of major concern for database

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ij - MIT OpenCourseWare

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Python Basic

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Intelligent data engineering
Intelligent data engineering

... composition of tree needles as they are aging. Different regression models have been compared to find out how these effects could be modeled effectively and accurately during the second year of the needles [3]. We found that sparse regression models are well suited for this kind of analysis. They ar ...
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week 14 Datamining print PPT95

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TUTORIAL 1 - Fundamentals

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slides - Methodologies to Improve big Data Projects

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Computation with Real Numbers

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No Slide Title

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IB - Course Outline_07-09

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Chapter 2: Fundamentals of the Analysis of Algorithm

... • Decide on a parameter indicating an input’s size. • Identify the algorithm’s basic operation. • Check whether the number of times the basic op. is executed may vary on different inputs of the same size. (If it may, the worst, average, and best cases must be investigated separately.) • Set up a rec ...
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Corecursion

In computer science, corecursion is a type of operation that is dual to recursion. Whereas recursion works analytically, starting on data further from a base case and breaking it down into smaller data and repeating until one reaches a base case, corecursion works synthetically, starting from a base case and building it up, iteratively producing data further removed from a base case. Put simply, corecursive algorithms use the data that they themselves produce, bit by bit, as they become available, and needed, to produce further bits of data. A similar but distinct concept is generative recursion which may lack a definite ""direction"" inherent in corecursion and recursion. Where recursion allows programs to operate on arbitrarily complex data, so long as they can be reduced to simple data (base cases), corecursion allows programs to produce arbitrarily complex and potentially infinite data structures, such as streams, so long as it can be produced from simple data (base cases). Where recursion may not terminate, never reaching a base state, corecursion starts from a base state, and thus produces subsequent steps deterministically, though it may proceed indefinitely (and thus not terminate under strict evaluation), or it may consume more than it produces and thus become non-productive. Many functions that are traditionally analyzed as recursive can alternatively, and arguably more naturally, be interpreted as corecursive functions that are terminated at a given stage, for example recurrence relations such as the factorial.Corecursion can produce both finite and infinite data structures as result, and may employ self-referential data structures. Corecursion is often used in conjunction with lazy evaluation, to only produce a finite subset of a potentially infinite structure (rather than trying to produce an entire infinite structure at once). Corecursion is a particularly important concept in functional programming, where corecursion and codata allow total languages to work with infinite data structures.
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