Search Results: 'Data Dependence'

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37 results for "Data Dependence"
Collection of a Variety of Data By Homework Help Classof1
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To make a decision in any business situation everybody needs a data and the facts expressed in quantitative form can be termed as data. Success of any statistical investigation depends on the... More > availability of accurate and reliable data. These depend on the appropriateness of the method chosen for data collection. Therefore, data collection is a very basic activity in decision making.< Less
Methods of Collecting Primary and Secondary Data By Homework Help Classof1
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To make a decision in any business situation everybody needs a data and the facts expressed in quantitative form can be termed as data. Success of any statistical investigation depends on the... More > availability of accurate and reliable data. These depend on the appropriateness of the method chosen for data collection. Therefore, data collection is a very basic activity in decision making.< Less
Introduction to Social Informatics: Data Networks Programs By Dmitry Zinoviev
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This book is an introduction to social informatics. "Can they steal my identity " - "What does it mean encryption " - "How do Web chats work " - "What is a virus... More > " - "Who's spying on my computer " - These and many other questions are becoming important and sometimes vitally important for people who thought they had nothing to do with the computing profession. As computers and other computing devices penetrate deeper and deeper into our everyday life, we become more and more dependent on them. The purpose of this book is to show what's "running under the hood" of a computer and a computer network, where are the threats coming from, how to avoid them, and how the advent of computers and networks is changing our society.< Less
Learning with Structured Data: Applications to Computer Vision By Sebastian Nowozin
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This thesis addresses structured machine learning problems. Here "structured" refers to situations in which the input or output domain of a prediction function is non-vectorial. Instead,... More > the input instance or the predicted value can be decomposed into parts that follow certain dependencies, relations and constraints. The first part of the thesis considers structure in the input domain and a general framework based on the notion of substructures is developed. The framework is broadly applicable and two computer vision problems illustrate this: class-level object recognition and human action recognition. The second part of the thesis addresses structure in the output domain of a prediction function. Specifically image segmentation problems in which the produced segmentation must satisfy global properties such as connectivity are analyzed. As a result, a principled method to incorporate global interactions into computer vision random field models by means of linear programming relaxations is given.< Less
Learning with Structured Data: Applications to Computer Vision By Sebastian Nowozin
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This thesis addresses structured machine learning problems. Here "structured" refers to situations in which the input or output domain of a prediction function is non-vectorial. Instead,... More > the input instance or the predicted value can be decomposed into parts that follow certain dependencies, relations and constraints. The first part of the thesis considers structure in the input domain and a general framework based on the notion of substructures is developed. The framework is broadly applicable and two computer vision problems illustrate this: class-level object recognition and human action recognition. The second part of the thesis addresses structure in the output domain of a prediction function. Specifically image segmentation problems in which the produced segmentation must satisfy global properties such as connectivity are analyzed. As a result, a principled method to incorporate global interactions into computer vision random field models by means of linear programming relaxations is given.< Less
Data Deduplication: High-impact Strategies - What You Need to Know: Definitions, Adoptions, Impact, Benefits, Maturity, Vendors By Kevin Roebuck
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Data deduplication is a specialized data compression technique for eliminating coarse-grained redundant data, typically to improve storage utilization. In the deduplication process, duplicate data is... More > deleted, leaving only one copy of the data to be stored, along with references to the unique copy of data. Deduplication is able to reduce the required storage capacity since only the unique data is stored. Depending on the type of deduplication, redundant files may be reduced, or even portions of files or other data that are similar can also be removed. As a simple example of file based deduplication, a typical email system might contain 100 instances of the same one megabyte (MB) file attachment. If the email platform is backed up or archived, all 100 instances are saved, requiring 100 MB storage space. This book is your ultimate resource for Data Deduplication. Here you will find the most up-to-date information, analysis, background and everything you need to know.< Less
HC-CS-TR-2010-01: A Retrospective of the Omega Project By Haverford College
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Haverford College Technical Report describing the major results of Bill Pugh's "Omega Project" at UMCP.
HC-CS-TR-2010-01: A Retrospective of the Omega Project By Haverford College
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Haverford College Technical Report describing the major results of Bill Pugh's "Omega Project" at UMCP.
Difference Between Two Population Means By Homework Help Classof1
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we describe estimation and hypothesis-testing procedures for the difference between two population means when the samples are dependent. In a case of two dependent samples, two data values—one... More > for each sample—are collected from the same source (or element) and, hence, these are also called paired or matched samples.< Less
IGOR Pro 6 Manual - Programming - Volume IV By WaveMetrics, Inc.
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IGOR Pro 6.3 Manual Programming, Volume 4 of 6. Topics include: Working with Commands, Programming Overview, User-Defined Functions, Macros, User-Defined Menus, Interacting with the User,... More > Programming Techniques, Debugging, Dependencies, and Advanced Programming.< Less