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blog/2015/10/auto-diff-in-julia.md

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Notice that our dual number result comes *close* to the result obtained from Calculus.jl, but is actually slightly different. That slight difference is due to the approximation error inherent to the finite differencing method employed by Calculus.jl.
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In reality, the number types that ForwardDiff.jl provides are quite a bit more complicated than `DualNumber`. Instead of simple dual numbers, the various `ForwardDiffNumber` types behave like *ensembles* of dual numbers and [hyper-dual numbers](https://adl.stanford.edu/hyperdual/Fike_AIAA-2011-886.pdf) (the higher-order analog of dual numbers). This ensemble-based approach allows for simultaneous calculation of multiple higher-order partial derivatives in a single evaluation of the target function. For an in-depth examination of ForwardDiff.jl's number type implementation, see [this section of the developer documentation](https://www.juliadiff.org/ForwardDiff.jl/types.html).
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In reality, the number types that ForwardDiff.jl provides are quite a bit more complicated than `DualNumber`. Instead of simple dual numbers, the various `ForwardDiffNumber` types behave like *ensembles* of dual numbers and [hyper-dual numbers](http://adl.stanford.edu/hyperdual/Fike_AIAA-2011-886.pdf) (the higher-order analog of dual numbers). This ensemble-based approach allows for simultaneous calculation of multiple higher-order partial derivatives in a single evaluation of the target function. For an in-depth examination of ForwardDiff.jl's number type implementation, see [this section of the developer documentation](https://www.juliadiff.org/ForwardDiff.jl/types.html).
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# Performance Comparison: The Ackley Function
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blog/2015/10/biojulia-sequence-analysis.md

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genome-scale (about 3.2 billions length for human), a full-text search index is
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used to speed up this alignment process. This kind of full-text search index
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is implemented in many bioinformatics tools, most notably
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[bowtie2](https://bowtie-bio.sourceforge.net/bowtie2/index.shtml) and
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[BWA](https://bio-bwa.sourceforge.net/), whose papers are cited thousands of
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[bowtie2](http://bowtie-bio.sourceforge.net/bowtie2/index.shtml) and
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[BWA](http://bio-bwa.sourceforge.net/), whose papers are cited thousands of
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times.
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![Mapping](/assets/blog/2015-10-03-sequence-analysis/mapping.png)

blog/2018/03/pifonts.md

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![accumulating pi](/assets/blog/2018-04-13-pifonts/accumulate-pi.png)
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For a complete font based on the average shapes of many other fonts, have a look at [Averia](https://www.iotic.com/averia/).
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For a complete font based on the average shapes of many other fonts, have a look at [Averia](http://iotic.com/averia/).
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I haven't yet found a way to list all the fonts that contain the full set of Unicode π symbols. In theory I think I can use [Freetype.jl](https://github.com/juliagraphics/FreeType.jl) to inspect a font to see whether it contains code points for particular character glyphs. Perhaps I’ll report back on 3-14-19 with any progress…

blog/2018/06/missing.md

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missing values. Being essential for statistical analyses and data management,
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this feature is common among specialized languages, such as
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[SQL](https://en.wikipedia.org/wiki/Null_(SQL)) (with the `NULL` value),
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[R](https://cran.r-project.org/doc/manuals/r-release/R-lang.html#NA-handling) (`NA`),
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[R](http://cran.r-project.org/doc/manuals/r-release/R-lang.html#NA-handling) (`NA`),
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[SAS](https://support.sas.com/documentation/cdl/en/lrcon/62955/HTML/default/viewer.htm#a001292604.htm)
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(`.`, `' '`, etc.) or
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[Stata](https://www.stata.com/support/faqs/data-management/logical-expressions-and-missing-values/)

blog/2018/08/GSoC-Final-Summary.md

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@def rss_pubdate = Date(2018, 8, 6)
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@def rss = """ GSoC 2018: Reinforcement Learning and Generative models using Flux | In this post I'm going to briefly summarize about the machine learning models I have worked on during this summer for GSoC. I worked towards enriching model zoo of Flux.jl (https://github.com/FluxML), a machine learning library written in Julia (https://github.com/julia/julialang). My project cover... """
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@def rss = """ GSoC 2018: Reinforcement Learning and Generative models using Flux | In this post I'm going to briefly summarize about the machine learning models I have worked on during this summer for GSoC. I worked towards enriching model zoo of Flux.jl (https://github.com/FluxML), a machine learning library written in Julia (https://github.com/JuliaLang/julia). My project cover... """
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@def published = "6 August 2018"
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@def title = "GSoC 2018: Reinforcement Learning and Generative models using Flux"
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@def authors = """ <a href="https://github.com/tejank10">Tejan Karmali</a>"""
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Hello, world!
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In this post I'm going to briefly summarize about the machine learning models I have worked on during this summer for GSoC. I worked towards enriching model zoo of [Flux.jl](https://github.com/FluxML), a machine learning library written in [Julia](https://github.com/julia/julialang). My project covered Reinforcement Learning and computer vision models.
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In this post I'm going to briefly summarize about the machine learning models I have worked on during this summer for GSoC. I worked towards enriching model zoo of [Flux.jl](https://github.com/FluxML), a machine learning library written in [Julia](https://github.com/JuliaLang/julia). My project covered Reinforcement Learning and computer vision models.
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The project is spread over these 4 codebases
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1. [Flux-baselines](https://github.com/tejank10/Flux-baselines)
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#### Future Work
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1. Add more variety of models, especially the ones which have come up in the last 18 months.
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2. Create an interface to easily train and test any environment from [OpenAIGym.jl](https://github.com.JuliaML/OpenAIGym.jl).
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2. Create an interface to easily train and test any environment from [OpenAIGym.jl](https://github.com/JuliaML/OpenAIGym.jl).
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## 2. AlphaGo.jl
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## Acknowledgements
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I really would like to thank my mentor [Mike Innes](https://github.com/MikeInnes) for guiding me throughout the project, and [James Bradbury](https://github.om/jekbradbury) for his valuable inputs for improving the code in the Reinforcement Learning models. I also would like to thank [Neethu Mariya Joy](https://github.com/roboneet) for deploying the trained models on the web. And last but not the least, The Julia Project and NumFOCUS: for sponsoring me and all other JSoC students for JuliaCon'18 London.
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I really would like to thank my mentor [Mike Innes](https://github.com/MikeInnes) for guiding me throughout the project, and [James Bradbury](https://github.com/jekbradbury) for his valuable inputs for improving the code in the Reinforcement Learning models. I also would like to thank [Neethu Mariya Joy](https://github.com/roboneet) for deploying the trained models on the web. And last but not the least, The Julia Project and NumFOCUS: for sponsoring me and all other JSoC students for JuliaCon'18 London.

blog/2019/07/multithreading-zh-cn.md

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如果您在使用 Julia 中的线程时遇到任何问题,请在[GitHub][]或我们的[论坛][Discourse]中告知我们!
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[free lunch]: https://www.gotw.ca/publications/concurrency-ddj.htm
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[free lunch]: http://www.gotw.ca/publications/concurrency-ddj.htm
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[Cilk]: http://supertech.csail.mit.edu/cilk/
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[Intel Threading Building Blocks]: https://software.intel.com/en-us/intel-tbb/
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blog/2019/07/multithreading.md

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[free lunch]: https://www.gotw.ca/publications/concurrency-ddj.htm
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[free lunch]: http://www.gotw.ca/publications/concurrency-ddj.htm
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[Cilk]: http://supertech.csail.mit.edu/cilk/
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blog/2019/09/profilers.md

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@def rss = """ Profiling tools are awesome. They let us see what actually is affecting our program performance. Profiling tools also are terrible. They lie to us and give us confusing information. They also have some surprisingly new developments: [brendangregg's often cloned flamegraphs tool](https://www.brendangregg.com/flamegraphs.html) was created in 2011! So here I will be investigating some ways to make our profile reports better; and looking at ways in which they commonly break, to raise awareness of those artifacts in the reports. ![Instruments.app bad result](/assets/blog/2019-09-16-profilers/profile-instruments-bad.png)"""
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@def rss = """ Profiling tools are awesome. They let us see what actually is affecting our program performance. Profiling tools also are terrible. They lie to us and give us confusing information. They also have some surprisingly new developments: [brendangregg's often cloned flamegraphs tool](http://www.brendangregg.com/flamegraphs.html) was created in 2011! So here I will be investigating some ways to make our profile reports better; and looking at ways in which they commonly break, to raise awareness of those artifacts in the reports. ![Instruments.app bad result](/assets/blog/2019-09-16-profilers/profile-instruments-bad.png)"""
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@def published = "16 September 2019"
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@def title = "Profiling tool wins and woes"
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@def authors = """<a href="https://github.com/vtjnash/">Jameson Nash</a>"""
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Profiling tools are awesome. They let us see what actually is affecting our program performance. Profiling tools also are terrible. They lie to us and give us confusing information. They also have some surprisingly new developments: [brendangregg's often cloned flamegraphs tool](https://www.brendangregg.com/flamegraphs.html) was created in 2011! So here I will be investigating some ways to make our profile reports better; and looking at ways in which they commonly break, to raise awareness of those artifacts in the reports.
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Profiling tools are awesome. They let us see what actually is affecting our program performance. Profiling tools also are terrible. They lie to us and give us confusing information. They also have some surprisingly new developments: [brendangregg's often cloned flamegraphs tool](http://www.brendangregg.com/flamegraphs.html) was created in 2011! So here I will be investigating some ways to make our profile reports better; and looking at ways in which they commonly break, to raise awareness of those artifacts in the reports.
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## Learn more!
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- Julia Evans on learning to be a wizard: <https://wizardzines.com/zines/perf/>
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- Julia Evans taking a sabbatical to write a profiler tool: <https://jvns.ca/categories/ruby-profiler/>
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- Brendan Gregg on perf: <https://www.brendangregg.com/perf.html>
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- Brendan Gregg on flamegraphs: <https://www.brendangregg.com/flamegraphs.html>
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- Brendan Gregg on flamegraphs: <http://www.brendangregg.com/flamegraphs.html>
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Then come back here to dive deeper!
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learning/index.md

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* [CS 5220](https://www.cs.cornell.edu/~bindel/class/cs5220-s14/), Applications of Parallel Computers (Prof. David Bindel), Spring 2014
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* École Polytechnique Fédérale de Lausanne
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* [CIVIL 557] Decision-aid methodologies in transportation (Mor Kaspi, Virginie Lurkin), Spring 2017
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* [Einaudi Institute for Economics and Finance, Rome](https://www.eief.it/eief/)
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* [Einaudi Institute for Economics and Finance, Rome](http://www.eief.it/eief/)
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* [Econometrics of DSGE Models](https://gragusa.org/teaching/eief-dsge/) ([Giuseppe Ragusa](http://gragusa.org))
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* Emory University
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* [MATH 346](https://www.mathcs.emory.edu/~lruthot/courses/sp15-math346.html), Introduction to Optimization Theory (Prof. Lars Ruthotto), Spring 2015
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* [MATH 516](https://www.mathcs.emory.edu/~lruthot/courses/math516.html), Numerical Analysis II (Prof. Lars Ruthotto), Spring 2015
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* Federal Rural University of Rio de Janeiro (UFRRJ)
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* TM429, Introduction to Recommender Systems (Prof. [Filipe Braida](https://github.com/filipebraida)), Fall 2016, Spring 2017
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* [Federal University of Alagoas](https://www.ufal.edu.br) (_Universidade Federal de Alagoas_, UFAL)
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* [Federal University of Alagoas](https://ufal.br) (_Universidade Federal de Alagoas_, UFAL)
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* COMP272, Distributed Systems ([Prof. André Lage-Freitas](https://sites.google.com/a/ic.ufal.br/andrelage)): 2015, 2016, and 2017
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* [Federal University of Paraná](https://www.ufpr.br/) (_Universidade Federal do Paraná_, UFPR)
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* CM103, Mathematics Laboratory ([Prof. Abel Soares Siqueira](https://abelsiqueira.github.io/)): 2016, 2017, and 2018
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* Hadsel High School, Stokmarknes, Nordland, Norway
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* [AnsattOversikt](https://www.hadsel.vgs.no/AnsattOversikt.aspx?personid=16964&amp;mid1=15925), [REA3034] Programmering og modellering (Programming and modeling with Julia and Snap), 2018 / 19 (High school lecturer Olav A Marschall, M.sc. Computer Science)
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* IIT Indore
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* [ApplNLA](https://github.com/ivanslapnicar/GIAN-Applied-NLA-Course), Modern Applications of Numerical Linear Algebra (Prof. [Ivan Slapnicar](https://marjan.fesb.hr/~slap/)), June 2016
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* [ApplNLA](https://github.com/ivanslapnicar/GIAN-Applied-NLA-Course), Modern Applications of Numerical Linear Algebra (Prof. [Ivan Slapnicar](http://marjan.fesb.hr/~slap/)), June 2016
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* Iowa State University
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* [STAT 590F](https://github.com/heike/stat590f), Topics in Statistical Computing: Julia Seminar (Prof. Heike Hofmann), Fall 2014
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* [Luiss University Rome](https://www.luiss.edu/), [Department of Economics and Finance](https://economiaefinanza.luiss.it)
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* CHEG 5395, Metaheuristic and Heuristic Methods in Chemical Engineering (Prof. Ranjan Srivastava), Spring 2018
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* University of Edinburgh
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* Spring 2017, [MATH11146](https://www.drps.ed.ac.uk/16-17/dpt/cxmath11146.htm), Modern optimization methods for big data problems (Prof. [Peter Richtarik](https://www.maths.ed.ac.uk/~prichtar/index.html))
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* Spring 2016, [MATH11146](https://www.drps.ed.ac.uk/15-16/dpt/cxmath11146.htm), Modern optimization methods for big data problems (Prof. [Peter Richtarik](https://www.maths.ed.ac.uk/~prichtar/index.html))
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* Spring 2016, [MATH11146](http://www.drps.ed.ac.uk/15-16/dpt/cxmath11146.htm), Modern optimization methods for big data problems (Prof. [Peter Richtarik](https://www.maths.ed.ac.uk/~prichtar/index.html))
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* University of Glasgow, School of Mathematics and Statistics
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* An Introduction to Julia, course of Online Master of Science (MSc) in Data Analytics ([Theodore Papamarkou](https://www.gla.ac.uk/postgraduate/taught/dataanalytics/)), September 2017
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* University of Oulu
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* Université Paul Sabatier, Toulouse
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* [Optimization in Machine Learning](https://www.irit.fr/cimi-machine-learning/node/15.html), (Prof. [Peter Richtarik](https://www.maths.ed.ac.uk/~prichtar/)), Fall 2015
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* [Université de Liège](https://www.ulg.ac.be/)
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* [MATH0462](https://www.montefiore.ulg.ac.be/~tcuvelier/teaching/2016-2017-discrete-optimisation), Discrete Optimization (Prof. [Quentin Louveaux](https://www.montefiore.ulg.ac.be/~louveaux/)), Fall 2016
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* [MATH0461](https://www.programmes.uliege.be/cocoon/20192020/cours/MATH0461-2.html), Introduction to Numerical Optimization (Prof. [Quentin Louveaux](https://www.montefiore.ulg.ac.be/~louveaux/)), Fall 2016
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* [MATH0462](https://www.montefiore.ulg.ac.be/~tcuvelier/teaching/2015-2016-discrete-optimisation), Discrete Optimization (Prof. [Quentin Louveaux](https://www.montefiore.ulg.ac.be/~louveaux/)), Fall 2015
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* [MATH0462](http://www.tcuvelier.be/teaching-2016-2017-discrete-optimisation), Discrete Optimization (Prof. [Quentin Louveaux](http://www.montefiore.ulg.ac.be/~louveaux/)), Fall 2016
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* [MATH0461](https://www.programmes.uliege.be/cocoon/20192020/cours/MATH0461-2.html), Introduction to Numerical Optimization (Prof. [Quentin Louveaux](http://www.montefiore.ulg.ac.be/~louveaux/)), Fall 2016
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* [MATH0462](https://www.montefiore.ulg.ac.be/~tcuvelier/teaching/2015-2016-discrete-optimisation), Discrete Optimization (Prof. [Quentin Louveaux](http://www.montefiore.ulg.ac.be/~louveaux/)), Fall 2015
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* Université de Montréal
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* [IFT1575](https://admission.umontreal.ca/cours-et-horaires/cours/IFT-1575/), Modèles de recherche opérationnelle (Prof. [Bernard Gendron](https://www.iro.umontreal.ca/~gendron/)), Fall 2017
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* [IFT3245](https://admission.umontreal.ca/cours-et-horaires/cours/IFT-3245/), Simulation et modèles (Prof. [Fabian Bastin](https://www.iro.umontreal.ca/~bastin/)), Fall 2017

research.md

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* **Forward stable computation of roots of real polynomials with only real distinct roots**. N. Jakovčević Stor, I. Slapničar. (2015): 1&ndash;15. doi: [10.18576/amis/110105](https://dx.doi.org/10.18576/amis/110105). arXiv: [1509.06224](https://arxiv.org/abs/1509.06224). Packages: [Arrowhead.jl](https://github.com/ivanslapnicar/Arrowhead.jl).
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* **Forward stable eigenvalue decomposition of rank-one modifications of diagonal matrices**. N. Jakovčević Stor, I. Slapničar, J. L. Barlow. (2015) _Linear Algebra and its Applications_, 487: 301&ndash;315. doi: [10.1016/j.laa.2015.09.025](https://dx.doi.org/10.1016/j.laa.2015.09.025). Packages: [Arrowhead.jl](https://github.com/ivanslapnicar/Arrowhead.jl).
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* **Is High Temporal Resolution Achievable for Paediatric Cardiac Acquisitions during Several Heart Beats? Illustration with Cardiac Phase Contrast Cine-MRI**. Laurent Bonnemains, Freddy Odille, Christophe Meyer, Gabriella Hossu, Jacques Felblinger, Pierre-André Vuissoz. (2015) _PLoS ONE_, 10. doi: [10.1371/journal.pone.0143744](https://dx.doi.org/10.1371/journal.pone.0143744).
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* **Matrix Depot: An Extensible Test Matrix Collection for Julia**. Zhang, Weijian, Higham, Nicholas J.. (2015) _MIMS EPrint_, 2015.118. doi: [10.7717/peerj-cs.58](https://dx.doi.org/10.7717/peerj-cs.58). url: [https://eprints.ma.man.ac.uk/2426](https://eprints.ma.man.ac.uk/2426). Packages: [MatrixDepot.jl](https://github.com/weijianzhang/MatrixDepot.jl).
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* **Matrix Depot: An Extensible Test Matrix Collection for Julia**. Zhang, Weijian, Higham, Nicholas J.. (2015) _MIMS EPrint_, 2015.118. doi: [10.7717/peerj-cs.58](https://dx.doi.org/10.7717/peerj-cs.58). url: [http://eprints.ma.man.ac.uk/2426](http://eprints.ma.man.ac.uk/2426). Packages: [MatrixDepot.jl](https://github.com/weijianzhang/MatrixDepot.jl).
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* **Monte Carlo Methods and Zero Variance Principle**. Theodore Papamarkou, Antonietta Mira, Mark Girolami. (2015), Current Trends in Bayesian Methodology with Applications: 457&ndash;476.
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