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Peekaboo | peekaboo-vision.blogspot.com Reviews

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Andy&#39;s Computer Vision and Machine Learning Blog

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1

Peekaboo: Restricted Boltzmann Machine on CUDA with Python

http://peekaboo-vision.blogspot.com/2010/11/restricted-boltzmann-machine-on-cuda.html

Andy's Computer Vision and Machine Learning Blog. Monday, November 8, 2010. Restricted Boltzmann Machine on CUDA with Python. As promised, my group. Recently published our Restricted Boltzmann Machine implementation. It is based upon the CUV Library. That is being developed here. The idea is to combine the ease of programming of Python with the computing power of the GPU. We used this implementation for several papers and it grew a lot over time. Here is a list of most of the features:. Comments are very...

2

Peekaboo: ICML 2013 Reading List

http://peekaboo-vision.blogspot.com/2013/07/icml-2013-reading-list.html

Andy's Computer Vision and Machine Learning Blog. Tuesday, July 2, 2013. ICML 2013 Reading List. The ICML is now already over for two weeks, but I still wanted to write about my reading list, as there have been some quite interesting papers ( the proceedings are here. Also, I haven't blogged in ages, for which I really have no excuse ;). Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures. James Bergstra, Daniel Yamins, David Cox. Li Wan, Matth...

3

Peekaboo: Kernel Approximations for Efficient SVMs (and other feature extraction methods) [update]

http://peekaboo-vision.blogspot.com/2012/12/kernel-approximations-for-efficient.html

Andy's Computer Vision and Machine Learning Blog. Wednesday, December 26, 2012. Kernel Approximations for Efficient SVMs (and other feature extraction methods) [update]. Recently we added another method for kernel approximation, the Nyström method, to scikit-learn. Which will be featured in the upcoming 0.13 release. Kernel-approximations were my first somewhat bigger contribution to scikit-learn and I have been thinking about them for a while. There is obviously no way this can be linearly separated.

4

Peekaboo: Recap of my first Kaggle Competition: Detecting Insults in Social Commentary [update 3]

http://peekaboo-vision.blogspot.com/2012/09/recap-of-my-first-kaggle-competition.html

Andy's Computer Vision and Machine Learning Blog. Saturday, September 22, 2012. Recap of my first Kaggle Competition: Detecting Insults in Social Commentary [update 3]. Recently I entered my first kaggle. Competition - for those who don't know it, it is a site running machine learning competitions. A data set and time frame is provided and the best submission gets a money prize, often something between 5000$ and 50000$. My weapon of choice was Python with scikit-learn. The Result (Spoiler alert). I made ...

5

Peekaboo: Machine Learning Cheat Sheet (for scikit-learn)

http://peekaboo-vision.blogspot.com/2013/01/machine-learning-cheat-sheet-for-scikit.html

Andy's Computer Vision and Machine Learning Blog. Friday, January 25, 2013. Machine Learning Cheat Sheet (for scikit-learn). As you hopefully have heard, we at scikit-learn. Are doing a user survey. Which is still open by the way). One of the requests there was to provide some sort of flow chart on how to do machine learning. As this is clearly impossible, I went to work straight away. This is the result:. Clarification: With ensemble classifiers and ensemble regressors I mean random forests. Which trans...

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I say things - SciPy

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

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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Publications

http://fa.bianp.net/pages/publications.html

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 - 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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Machine Learning Blogs – covert.io

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I am a developer and security researcher deeply interested in Big Data/cloud computing and machine Learning. Peekaboo: Andy’s Computer Vision and Machine Learning Blog. Machine Learning, etc. 2014 Jason Trost. Powered by Jekyll. Using the HPSTR Theme.

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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 - machine learning

http://fa.bianp.net/tag/machine-learning.html

A fast, fully asynchronous variant of the SAGA algorithm. Wed 12 October 2016. My friend Rémi Leblond. Has recently uploaded to ArXiv our preprint on an asynchronous version of the SAGA optimization algorithm. The main contribution is to develop a parallel (fully asynchronous, no locks) variant of the SAGA algorighm. The core of the asynchronous algorithm is similar to Hogwild! The speedups obtained versus the sequential version are quite impressive. For example, we have observed to commonly obtain 5...

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I say things - Python

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

Fri 25 March 2016. Announce: first public release of lightning. A library for large-scale linear classification, regression and ranking in Python. The library was started a couple of years ago by Mathieu Blondel. Who also contributed the vast majority of source code. I joined recently its development and decided it was about time for a v0.1! Prebuild conda packages are available for all operating systems (god thank appveyor). More information on lightning's website. Sun 06 March 2016. Mon 22 February 2016.

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I say things - Jupyter

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

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

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

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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Peekaboo

Andy's Computer Vision and Machine Learning Blog. Thursday, March 20, 2014. Off-topic: speed reading like spritz. As the title suggests, this is a non-machine-learning, non-vision, non-python post *gasp*. Some people in my network posted about spritz. A startup that recently went out of stealth-mode. They do a pretty cool app for speed reading. See this huffington post article. For a quick demo and explanation. They say they are still in development, so the app is not available for the public. The code i...

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