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Название: Towards Efficient Exploitation of GPUs
Автор: Jacobo Lobeiras Blanco
Издательство: Universidade da Coru?a
Год: 2014
Формат: pdf
Страниц: 222
Размер: 9,6 mb.
Язык: English
GPU computing supposed a major step forward, bringing high performance computing to commodity hardware. Feature-rich parallel languages like CUDA and OpenCL reduced the programming complexity. However, to fully take advantage of their computing power, specialized parallel algorithms are required. Moreover, the complex GPU memory hierarchy and highly threaded architecture makes programming a difficult task even for experienced programmers. Due to the novelty of GPU programming, common general purpose libraries are scarce and parallel versions of the algorithms are not always readily available. | |
Разместил: Semka 11-01-2019, 12:21 | Комментарии: 0 | Подробнее
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Название: Think Complexity 2
Автор: Allen B. Downey
Издательство: Green Tea Press
Год: 2016
Формат: pdf
Страниц: 214
Размер: 1,4 mb.
Язык: English
This book is primarily about complexity science, but it is also about data structures and algorithms, intermediate programming in Python, computational modeling, and the philosophy of science. | |
Разместил: Semka 11-01-2019, 12:20 | Комментарии: 0 | Подробнее
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Название: Handbook Statistical foundations of machine learning
Автор: Gianluca Bontempi
Издательство: Universite Libre de Bruxelles
Год: 2013
Формат: pdf
Страниц: 267
Размер: 7,07 mb.
Язык: English
In recent years, a growing number of organizations have been allocating vast amount of resources to construct and maintain databases and data warehouses. In scientific endeavours, data refers to carefully collected observations about some phenomenonunder study. In business, data capture information about economic trends, critical markets, competitors and customers. In manufacturing, data record machinery performances and production rates in different conditions. There are essentially two reasons why people gather increasing volumes of data: first, they think some valuable assets are implicitly coded within them, and computer technology enables effective data storage at reduced costs. | |
Разместил: Semka 11-01-2019, 12:20 | Комментарии: 0 | Подробнее
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Название: Statistical Learning and Sequential Prediction
Автор: Alexander Rakhlin , Karthik Sridharan
Издательство: Autoedici?n
Год: 2014
Формат: pdf
Страниц: 261
Размер: 2,4 mb.
Язык: English
This course will focus on theoretical aspects of Statistical Learning and Sequential Prediction. Until recently, these two subjects have been treated separately within the learning community. The course will follow a unified approach to analyzing learning in both scenarios. To make this happen, we shall bring together ideas from probability and statistics, game theory, algorithms, and optimization. It is this blend of ideas that makes the subject interesting for us, and we hope to convey the excitement. We shall try to make the course as self-contained as possible, and pointers to additional readings will be provided whenever necessary. Our target audience is graduate students with a solid background in probability and linear algebra. | |
Разместил: Semka 11-01-2019, 12:20 | Комментарии: 0 | Подробнее
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Название: Probabilistic Programming for Procedural Modeling and Design
Автор: Daniel Ritchie
Издательство: Standford University
Год: 2016
Формат: pdf
Страниц: 152
Размер: 43 mb.
Язык: English
Procedural modeling, or the use of pseudo-random programs to generate visual content, plays an important role in computer graphics and design. It facilitates content creation at massive scales, can automatically create painstakingly-detailed imagery, and can even generate pleasantly surprising results that can help people to navigate large and unintuitive design spaces | |
Разместил: Semka 11-01-2019, 12:20 | Комментарии: 0 | Подробнее
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Название: Parallel Cryptanalysis
Автор: Ruben Niederhagen
Издательство: Autoedici?n
Год: 2012
Формат: pdf
Страниц: 125
Размер: 0,8 mb.
Язык: English
Most of today’s cryptographic primitives are based on computations that are hard to perform for a potential attacker but easy to perform for somebody who is in possession of some secret information, the key, that opens a back door in these hard computations and allows them to be solved in a small amount of time. Each cryptographic primitive should be designed such that the cost of an attack grows exponentially with the problem size, while the computations using the secret key only grow polynomially. To estimate the strength of a cryptographic primitive it is important to know how hard it is to perform the computation without knowledge of the secret back door and to get an understanding of how much money or time the attacker has to spend. Usually a cryptographic primitive allows the cryptographer to choose parameters that make an attack harder at the cost of making the computations using the secret key harder as well. Therefore designing a cryptographic primitive imposes the dilemma of choosing the parameters strong enough to resist an attack up to a certain cost while choosing them small enough to allow usage of the primitive in the real world, e.g. on small computing devices like smart phones. | |
Разместил: Semka 11-01-2019, 12:19 | Комментарии: 0 | Подробнее
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Название: Multiobjective Analysis and Inference of Phylogenetic Hypotheses by Means of Parallel and Bioinspired Computing
Автор: Sergio Santander Jim?nez
Издательство: Universidad de Extremadura
Год: 2015
Формат: pdf
Страниц: 271
Размер: 10,3 mb.
Язык: English
One of the most outstanding research topics in the field of bioinformatics is the reconstruction of evolutionary relationships among species. By studying the molecular features of living organisms, phylogenetic inference procedures seek to provide hypotheses about the evolutionary events which led to the current biodiversity in nature. The result of a phylogenetic analysis is given by a treeshaped data structure known as phylogenetic tree, whose topology describes the evolutionary history of the input species by defining ancestor-descendant relationships. The biological quality of the inferred phylogenies is usually evaluated by means of optimality criteria, which allow the modelling of phylogenetic inference as an optimization problem. | |
Разместил: Semka 11-01-2019, 12:19 | Комментарии: 0 | Подробнее
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Название: Labs for Foundations of Applied Mathematics Volume III: Modeling with Uncertainty and Data
Автор: Various
Издательство: Autoedici?n
Год: 2016
Формат: pdf
Страниц: 239
Размер: 2,1 mb.
Язык: English
This lab manual is designed to accompany the textbook Foundations of Applied Mathematics by Humpherys and Jarvis.
Contents:
SQL
Intro to pandas
State Machines
Web Scraping
Web Technologies
Introduction to Parallel Programming
Collective Communication in Parallel Programs
MongoDB
Principal Component Analysis
Latent Semantic Indexing
Kalman Filter
Projectile Tracking
HMM State Estimation
English Language
HMM Parameter Estimation
Russian Alphabet
CDHMM Generation
Speech Recognition
Bayesian Updates
Bayesian Search
Metropolis Algorithm
Ising Model
Gibbs Sampling
Latent Dirichlet Allocation
K-Means Clustering
Gaussian Mixture Models
Crime Mapping
Classification Trees
Random Forests
K-Nearest Neighbors and Support Vector Machines
Image Recognition Tasks | |
Разместил: Semka 11-01-2019, 12:19 | Комментарии: 0 | Подробнее
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Название: From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science
Автор: Norm Matloff
Издательство: University of California
Год: 2016
Формат: pdf
Страниц: 409
Размер: 2,07 mb.
Язык: English
The materials here form a textbook for a course in mathematical probability and statistics for computer science students. (It would work fine for general students too.) | |
Разместил: Semka 11-01-2019, 12:19 | Комментарии: 0 | Подробнее
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Название: Data-Intensive Text Processing with MapReduce
Автор: Jimmy Lin , Chris Dyer
Издательство: Morgan & Claypool Publishers
Год: 2010
Формат: pdf
Страниц: 175
Размер: 1,3 mb.
Язык: English
Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. | |
Разместил: Semka 11-01-2019, 12:18 | Комментарии: 0 | Подробнее
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