This document provides a summary of online algorithms and introduces various tools for analyzing online algorithms, including potential functions, work functions, linear programming, and the classify and randomly select technique. It begins with an example of the ski rental problem and how it can be solved optimally using different online algorithms. It then outlines the main topics covered and provides examples to illustrate each technique. Potential functions are introduced using a list reorganization problem. Work functions are explained using a file migration problem on a graph. Linear programming is demonstrated for a fractional set cover problem. Finally, classify and randomly select is presented as the last technique for analyzing online algorithms.
Analysis and design of algorithms part2Deepak John
Analysis of searching and sorting. Insertion sort, Quick sort, Merge sort and Heap sort. Binomial Heaps and Fibonacci Heaps, Lower bounds for sorting by comparison of keys. Comparison of sorting algorithms. Amortized Time Analysis. Red-Black Trees – Insertion & Deletion.
Rajat Monga, Engineering Director, TensorFlow, Google at MLconf 2016MLconf
Machine Learning with TensorFlow: TensorFlow has enabled cutting-edge machine learning research at the top AI labs in the world. At the same time it has made the technology accessible to a large audience leading to some amazing uses. TensorFlow is used for classification, recommendation, text parsing, sentiment analysis and more. This talk will go over the design that makes it fast, flexible, and easy to use, and describe how we continue to make it better.
Avi Pfeffer, Principal Scientist, Charles River Analytics at MLconf SEA - 5/2...MLconf
Practical Probabilistic Programming with Figaro: Probabilistic reasoning enables you to predict the future, infer the past, and learn from experience. Probabilistic programming enables users to build and reason with a wide variety of probabilistic models without machine learning expertise. In this talk, I will present Figaro, a mature probabilistic programming system with many applications. I will describe the main design principles of the language and show example applications. I will also discuss our current efforts to fully automate and optimize the inference process.
(chapter 5) A Concise and Practical Introduction to Programming Algorithms in...Frank Nielsen
These are the slides accompanying the textbook:
A Concise and Practical Introduction to Programming Algorithms in Java
by Frank Nielsen
Published by Springer-Verlag (2009), Undergraduate textbook in computer science (UTiCS series)
ISBN: 978-1-84882-338-9
http://www.lix.polytechnique.fr/~nielsen/JavaProgramming/
http://link.springer.com/book/10.1007%2F978-1-84882-339-6
Algorithm Design and Complexity - Course 1&2Traian Rebedea
Courses 1 & 2 for the Algorithm Design and Complexity course at the Faculty of Engineering in Foreign Languages - Politehnica University of Bucharest, Romania
(Costless) Software Abstractions for Parallel ArchitecturesJoel Falcou
Performing large, intensive or non-trivial computing on array like data structures is one of the most common task in scientific computing, video game development and other fields. This matter of fact is backed up by the large number of tools, languages and libraries to perform such tasks. If we restrict ourselves to C++ based solutions, more than a dozen such libraries exists from BLAS/LAPACK C++ binding to template meta-programming based Blitz++ or Eigen. If all of these libraries provide good performance or good abstraction, none of them seems to fit the need of so many different user types.
Moreover, as parallel system complexity grows, the need to maintain all those components quickly become unwieldy. This talk explores various software design techniques - like Generative Programming, MetaProgramming and Generic Programming - and their application to the implementation of a parallel computing librariy in such a way that:
- abstraction and expressiveness are maximized - cost over efficiency is minimized
We'll skim over various applications and see how they can benefit from such tools. We will conclude by discussing what lessons were learnt from this kind of implementation and how those lessons can translate into new directions for the language itself.
Automatic Task-based Code Generation for High Performance DSELJoel Falcou
Providing high level tools for parallel programming while sustaining a high level of performance has been a challenge that techniques like Domain Specific Embedded Languages try to solve. In previous works, we investigated the design of such a DSEL – NT2 – providing a Matlab -like syntax for parallel numerical computations inside a C++ library.
Main issues addressed here is how liimtaions of classical DSEL generation and multithreaded code generation can be overcome.
Specifying function specializations over an arbitrary set of type constraints is a daunting task in C++ as soon as those constraints become more and more complex and/or grow in number. Various idioms are traditionally used to solve this problem: SFINAE or Tag Dispatching for example.
This talk introduces Boost.Dispatch, an infrastructure library that make Tag Dispatching easier to use and maintain by providing a protocol to define Tags and relationship between them, to map an arbitrary set of tags to a given function implementation and to extend said list of specialization in an open, modular way. The main new asset of Boost.Dispatch is the ability to use categorization of function properties and/or architectural information to guide the dispatch in addition to the more traditional use of type properties.
The talk will quickly brushes a picture of what SFINAE, overloading and Tag Dispatching mean in C++ and what are their limitations. We’ll introduce Boost.Dispatch over some examples ranging from simple library design to actual high performance computing code using the library to select best implementation of a function based on non-trivial architecture dependent information. Then we’ll dive into the implementation of the library and try to sketches the upcoming challenges yet to be solved.
HDR Defence - Software Abstractions for Parallel ArchitecturesJoel Falcou
Performing large, intensive or non-trivial computing on array like data
structures is one of the most common task in scientific computing, video game
development and other fields. This matter of fact is backed up by the large number
of tools, languages and libraries to perform such tasks. If we restrict ourselves to
C++ based solutions, more than a dozen such libraries exists from BLAS/LAPACK
C++ binding to template meta-programming based Blitz++ or Eigen.
If all of these libraries provide good performance or good abstraction, none of
them seems to fit the need of so many different user types. Moreover, as parallel
system complexity grows, the need to maintain all those components quickly
become unwieldy. This thesis explores various software design techniques - like
Generative Programming, MetaProgramming and Generic Programming - and their
application to the implementation of various parallel computing libraries in such a
way that abstraction and expressiveness are maximized while efficiency overhead is
minimized.
Analysis and design of algorithms part2Deepak John
Analysis of searching and sorting. Insertion sort, Quick sort, Merge sort and Heap sort. Binomial Heaps and Fibonacci Heaps, Lower bounds for sorting by comparison of keys. Comparison of sorting algorithms. Amortized Time Analysis. Red-Black Trees – Insertion & Deletion.
Rajat Monga, Engineering Director, TensorFlow, Google at MLconf 2016MLconf
Machine Learning with TensorFlow: TensorFlow has enabled cutting-edge machine learning research at the top AI labs in the world. At the same time it has made the technology accessible to a large audience leading to some amazing uses. TensorFlow is used for classification, recommendation, text parsing, sentiment analysis and more. This talk will go over the design that makes it fast, flexible, and easy to use, and describe how we continue to make it better.
Avi Pfeffer, Principal Scientist, Charles River Analytics at MLconf SEA - 5/2...MLconf
Practical Probabilistic Programming with Figaro: Probabilistic reasoning enables you to predict the future, infer the past, and learn from experience. Probabilistic programming enables users to build and reason with a wide variety of probabilistic models without machine learning expertise. In this talk, I will present Figaro, a mature probabilistic programming system with many applications. I will describe the main design principles of the language and show example applications. I will also discuss our current efforts to fully automate and optimize the inference process.
(chapter 5) A Concise and Practical Introduction to Programming Algorithms in...Frank Nielsen
These are the slides accompanying the textbook:
A Concise and Practical Introduction to Programming Algorithms in Java
by Frank Nielsen
Published by Springer-Verlag (2009), Undergraduate textbook in computer science (UTiCS series)
ISBN: 978-1-84882-338-9
http://www.lix.polytechnique.fr/~nielsen/JavaProgramming/
http://link.springer.com/book/10.1007%2F978-1-84882-339-6
Algorithm Design and Complexity - Course 1&2Traian Rebedea
Courses 1 & 2 for the Algorithm Design and Complexity course at the Faculty of Engineering in Foreign Languages - Politehnica University of Bucharest, Romania
(Costless) Software Abstractions for Parallel ArchitecturesJoel Falcou
Performing large, intensive or non-trivial computing on array like data structures is one of the most common task in scientific computing, video game development and other fields. This matter of fact is backed up by the large number of tools, languages and libraries to perform such tasks. If we restrict ourselves to C++ based solutions, more than a dozen such libraries exists from BLAS/LAPACK C++ binding to template meta-programming based Blitz++ or Eigen. If all of these libraries provide good performance or good abstraction, none of them seems to fit the need of so many different user types.
Moreover, as parallel system complexity grows, the need to maintain all those components quickly become unwieldy. This talk explores various software design techniques - like Generative Programming, MetaProgramming and Generic Programming - and their application to the implementation of a parallel computing librariy in such a way that:
- abstraction and expressiveness are maximized - cost over efficiency is minimized
We'll skim over various applications and see how they can benefit from such tools. We will conclude by discussing what lessons were learnt from this kind of implementation and how those lessons can translate into new directions for the language itself.
Automatic Task-based Code Generation for High Performance DSELJoel Falcou
Providing high level tools for parallel programming while sustaining a high level of performance has been a challenge that techniques like Domain Specific Embedded Languages try to solve. In previous works, we investigated the design of such a DSEL – NT2 – providing a Matlab -like syntax for parallel numerical computations inside a C++ library.
Main issues addressed here is how liimtaions of classical DSEL generation and multithreaded code generation can be overcome.
Specifying function specializations over an arbitrary set of type constraints is a daunting task in C++ as soon as those constraints become more and more complex and/or grow in number. Various idioms are traditionally used to solve this problem: SFINAE or Tag Dispatching for example.
This talk introduces Boost.Dispatch, an infrastructure library that make Tag Dispatching easier to use and maintain by providing a protocol to define Tags and relationship between them, to map an arbitrary set of tags to a given function implementation and to extend said list of specialization in an open, modular way. The main new asset of Boost.Dispatch is the ability to use categorization of function properties and/or architectural information to guide the dispatch in addition to the more traditional use of type properties.
The talk will quickly brushes a picture of what SFINAE, overloading and Tag Dispatching mean in C++ and what are their limitations. We’ll introduce Boost.Dispatch over some examples ranging from simple library design to actual high performance computing code using the library to select best implementation of a function based on non-trivial architecture dependent information. Then we’ll dive into the implementation of the library and try to sketches the upcoming challenges yet to be solved.
HDR Defence - Software Abstractions for Parallel ArchitecturesJoel Falcou
Performing large, intensive or non-trivial computing on array like data
structures is one of the most common task in scientific computing, video game
development and other fields. This matter of fact is backed up by the large number
of tools, languages and libraries to perform such tasks. If we restrict ourselves to
C++ based solutions, more than a dozen such libraries exists from BLAS/LAPACK
C++ binding to template meta-programming based Blitz++ or Eigen.
If all of these libraries provide good performance or good abstraction, none of
them seems to fit the need of so many different user types. Moreover, as parallel
system complexity grows, the need to maintain all those components quickly
become unwieldy. This thesis explores various software design techniques - like
Generative Programming, MetaProgramming and Generic Programming - and their
application to the implementation of various parallel computing libraries in such a
way that abstraction and expressiveness are maximized while efficiency overhead is
minimized.
How to star in your own radio show workshopLynda Brown
I will be conducting a workshop at the St Louis Public Library on Saturday, September 13th from 12pm-2pm CST on How to Star in Your Own Radio Show. I will be teaching participates how to create a blogtalkradio podcast. This workshop is open to the public.
The Invisible Enemies Series-Supernatural thrillers based on books from the B...Lynda Brown
The Invisible Enemies Series is a supernatural thriller series based on books from the Bible. Book one, Invisible Enemies is based on The Book of Job and book two, Seed of Satan:Leah's Story is based on Genesis 6, when the fallen angels commingled with human woman and gave bith to giants!
38 najboljih citata korscenih u seriji zlocinacki umovizeljkomiscevic
Postovani,
predstavljam vam 38 pazljivo odabranih mudrosti koje su obelezile prethodnih 6 sezona "Zlocinackih umova", a koje su ostavile najjaci utisak na mene!
Ko kaze da se gledanjem serija ne mogu nauciti pametne stvari? :)
TIME EXECUTION OF DIFFERENT SORTED ALGORITHMSTanya Makkar
what is Algorithm and classification and its complexity
Time Complexity
Time Space trade-off
Asymptotic time complexity of algorithm and its notation
Why do we need to classify running time of algorithm into growth rates?
Big O-h notation and example
Big omega notation and example
Big theta notation and its example
best among the 3 notation
finding complexity f(n) for certain cases
1. Average case
2.Best case
3.Worst case
Searching
Sorting
complexity of Sorting
Conclusion
1. A Toolbox for Online Algorithms Marcin Bieńkowski U niversity of Wroc ław phd open 2011
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40. LP: the algorithm (2) Observation 1: Generated primal solution is feasible Observation 2: Observation 3: Each constraint of the dual solution is violated at most by factor O(log m) Corollary: ALG is O(2 log m) = O(log m)-competitive
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