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CompSquad | Computational Group within the Chair Havas Dauphine

Computational Group within the Chair Havas Dauphine. June 11, 2016. Gave a short talk on lightning. A large-scale machine learning library for Python. Here are the slides and talk:. Lightning: large scale machine learning in python. SAGA algorithm in the lightning library. February 25, 2016. Cross-posted from fa.bianp.net. Recently we have implemented, (Fabian Pedregosa and Arnaud Rachez. Algorithm in the lightning. But it has the advantage with respect to SAG[. A small example, more as a sanity check th...

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CompSquad | Computational Group within the Chair Havas Dauphine | squad.compmath.fr Reviews
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Computational Group within the Chair Havas Dauphine. June 11, 2016. Gave a short talk on lightning. A large-scale machine learning library for Python. Here are the slides and talk:. Lightning: large scale machine learning in python. SAGA algorithm in the lightning library. February 25, 2016. Cross-posted from fa.bianp.net. Recently we have implemented, (Fabian Pedregosa and Arnaud Rachez. Algorithm in the lightning. But it has the advantage with respect to SAG[. A small example, more as a sanity check th...
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CompSquad | Computational Group within the Chair Havas Dauphine | squad.compmath.fr Reviews

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Computational Group within the Chair Havas Dauphine. June 11, 2016. Gave a short talk on lightning. A large-scale machine learning library for Python. Here are the slides and talk:. Lightning: large scale machine learning in python. SAGA algorithm in the lightning library. February 25, 2016. Cross-posted from fa.bianp.net. Recently we have implemented, (Fabian Pedregosa and Arnaud Rachez. Algorithm in the lightning. But it has the advantage with respect to SAG[. A small example, more as a sanity check th...

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Publications

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Here are my most recent publications. A similar list can also be found in my Google Scholar profile. On the convergence rate of the three operator splitting scheme. Word meaning in the ventral visual path: a perceptial to conceptual gradient of semantic coding.". Borghesani, Valentina, Fabian Pedregosa, Marco Buiatti, Alexis Amadon, Evelyn Eger, and Manuela Piazza. NeuroImage (2016) HTTP. Asaga: Asynchronous Parallel Saga. Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien, preprint, ArXiv. Borghesani,...

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I say things - SciPy

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Numerical optimizers for Logistic Regression. Mon 20 May 2013. In this post I compar several implementations of Logistic Regression. The task was to implement a Logistic Regression model using standard optimization tools from. And compare them against state of the art implementations such as LIBLINEAR. In this blog post I'll write down all the implementation details of this model, in the hope that not only the conclusions but also the process would be useful for future comparisons and benchmarks. Begin{a...

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I say things - Job

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Job Offer: data scientist in Paris. Fri 10 July 2015. And I are looking looking for a data scientist to work on large-scale non-smooth optimization methods and other topics. You can find more information in this link. The job description is intentionally vague, and depending on the candidate this can be a postdoc-like job with most of their time devoted to research or an engineering-like job with more emphasis on coding tasks and contributing to open source projects. Page 1 / 1.

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I say things - ranking

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Thu 02 May 2013. TL;DR: I've implemented a logistic ordinal regression or proportional odds model. Here is the Python code. Model, also known as the proportional odds was introduced in the early 80s by McCullagh [. And is a generalized linear model specially tailored for the case of predicting ordinal variables, that is, variables that are discrete (as in classification) but which can be ordered (as in regression). It can be seen as an extension of the logistic regression model to the ordinal setting.

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I say things - Jupyter

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Tue 21 April 2015. TL;DR I created a gallery for IPython/Jupyter notebooks. Check it out :-). A couple of months ago I put online a website that displays a collection of IPython/Jupyter notebooks. The is a website that collects user-submitted and publicly available notebooks and displays them with a nice screenshot. The great thing about this website compared to other. I would like to make a website where it is possible to. Under the hood there's a django app, for which the source code lives here. Don't ...

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I say things - fMRI

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Data-driven hemodynamic response function estimation. Fri 05 December 2014. My latest research paper. Deals with the estimation of the hemodynamic response function (HRF) from fMRI data. This is an important topic since the knowledge of a hemodynamic response function is what makes it possible to extract the brain activation maps that are used in most of the impressive applications of machine learning to fMRI, such as (but not limited to) the reconstruction of visual images from brain activity [.

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I say things - memory

http://fa.bianp.net/tag/memory.html

Different ways to get memory consumption or lessons learned from ` memory profiler`. Thu 25 July 2013. As part of the development of memory profiler. I've tried several ways to get memory usage of a program from within Python. In this post I'll describe the different alternatives I've tested. Is a python library that provides an interface for retrieving information on running processes. It provides convenient, fast and cross-platform functions to access the memory usage of a Python module:. From version ...

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I say things - consistency

http://fa.bianp.net/tag/consistency.html

On the consistency of ordinal regression methods. Fri 09 October 2015. My latests work (with Francis Bach. Is on the consistency of ordinal regression methods. It has the wildly imaginative title of "On the Consistency of Ordinal Regression Methods" and is currently under review but you can read the draft of it on ArXiv. If you have any thoughts about it, please leave me a comment! Having Fisher consistency is an important property that "allows us to design good loss functions with desirable properties"[.

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I say things - ordinal regression

http://fa.bianp.net/tag/ordinal-regression.html

Thu 02 May 2013. TL;DR: I've implemented a logistic ordinal regression or proportional odds model. Here is the Python code. Model, also known as the proportional odds was introduced in the early 80s by McCullagh [. And is a generalized linear model specially tailored for the case of predicting ordinal variables, that is, variables that are discrete (as in classification) but which can be ordered (as in regression). It can be seen as an extension of the logistic regression model to the ordinal setting.

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CompSquad | Computational Group within the Chair Havas Dauphine

Computational Group within the Chair Havas Dauphine. June 11, 2016. Gave a short talk on lightning. A large-scale machine learning library for Python. Here are the slides and talk:. Lightning: large scale machine learning in python. SAGA algorithm in the lightning library. February 25, 2016. Cross-posted from fa.bianp.net. Recently we have implemented, (Fabian Pedregosa and Arnaud Rachez. Algorithm in the lightning. But it has the advantage with respect to SAG[. A small example, more as a sanity check th...

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