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Slides
Slides

... – Start with random weights ri in range [1,c] – At any point in time wi = ri + ci Run with private • ci is # of times element ai was requested. counter – Arrange elements according to weights – Privacy: from privacy of counters • list depends on counters plus randomness ...
Tower of Hanoi Investigation 11/16/93
Tower of Hanoi Investigation 11/16/93

... Looking at the numbers, especially the ones you are sure of, do you see a pattern? Is there a formula? If n is the number of rings in the original stack, and H(n) is the minimum number of moves needed to transfer the stack to a different peg, then a formula is: H(n) = ...
halofix 90 50 v/ac (75 v/dc)
halofix 90 50 v/ac (75 v/dc)

Unit 3B Notes: Graphs of Polynomial Functions
Unit 3B Notes: Graphs of Polynomial Functions

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File System Examples

... Algorithm to ensure fragments only used for end of file Limit number of fragments per block to 2, 4, or 8 Keep track of free fragments ...
Data Sheet SOP for Function Testing Dissolved Oxygen Sensors
Data Sheet SOP for Function Testing Dissolved Oxygen Sensors

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5. Conditionals — How to Think Like a Computer Scientist: Learning

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A New Parallel Skeleton for General Accumulative Computations

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output - UCSB Computer Science

Week 6
Week 6

Pattern matching in concatenative programming languages
Pattern matching in concatenative programming languages

Java: Primitive Data Types, Variables and Constants Introduction
Java: Primitive Data Types, Variables and Constants Introduction

... Java, primitive data types are used to define variables and constants. A variable's or constant's data type indicates what sort of value it represents, such as whether it is an integer, a floating-point number or a character, and determines the values it may contain and the operations that may be pe ...
“Finding the right distribution” Dr. Peter Vanneck, Palisade Corporation
“Finding the right distribution” Dr. Peter Vanneck, Palisade Corporation

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Introduction to the multilayer perceptron

... The energy landscape The behaviour of a neural network as it attempts to arrive at a solution can be visualised in terms of the error or energy function Ep. The energy is a function of the input and the weights. For a given pattern, Ep can be plotted against the weights to give the so called energy ...
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Bayesian Challenges in Integrated Catchment Modelling

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Integrated household based agricultural survey methodology

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A Probabilistic Analysis for the Range Assignment - IIT-CNR

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PPT - Tandy Warnow

... 1.Remove the parsimony uninformative sites 2.Let I be the number of sites that support ((A,B),(C,D)) 3.Let J be the number of sites that support ((A,C),(B,D)) 4.Let K be the number of sites that support ((A,D),(B,C)) 5.Whichever tree is supported by the largest number of sites, return that tree. (Fo ...
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Exam and Answers for 1999/00

... c) Genetic algorithms are an example of a population based approach to problem solving. Give your ideas as to other potential population based approaches that could be used. Ideally you should not use the example that was presented in the lectures. The example given in the lectures was an approach b ...
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Streams

... Since the stream represents a function, we can write operations which work on functions and try to implement them in terms of the coefficients of the series. One such operation is integration. The integral of an infinite polynomial is also an infinite polynomial, but the coefficients will be differe ...
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Analysis 1, Solutions to ¨ Ubungsblatt Nr. 2

Show the result of evaluating each expression. Be sure that the
Show the result of evaluating each expression. Be sure that the

Sockets - cs.wisc.edu
Sockets - cs.wisc.edu

... – Applications use buffers as do protocols • Copies are VERY expensive • Message abstraction enables pointers to be used and minimal copies Fall, 2001 ...
6.037, IAP 2016—Streams 1 MASSACHVSETTS INSTITVTE OF TECHNOLOGY
6.037, IAP 2016—Streams 1 MASSACHVSETTS INSTITVTE OF TECHNOLOGY

... Since the stream represents a function, we can write operations which work on functions and try to implement them in terms of the coefficients of the series. One such operation is integration. The integral of an infinite polynomial is also an infinite polynomial, but the coefficients will be differe ...
Lecture 12 Data Reduction 1. Sufficient Statistics
Lecture 12 Data Reduction 1. Sufficient Statistics

< 1 ... 39 40 41 42 43 44 45 46 47 ... 124 >

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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