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An early overview of ICLR2019 (part 2)

Decisions for ICLR2019 are out! So it is time to take a look at this year’s trends! Which researches have been most successful? Which institutions? Which papers?

(Link to part 1)

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An early overview of ICLR2019

This year’s venue will be held on May 6-9 in New Orleans. No big changes with respect to the last edition, except for the Workshop track, which will be held in small concurrent events, with a separately chaired process. Anyway, let’s take a look to ICLR2019 reviews! For those who...

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An early overview of ICLR2018 (part 3)

Finally, decisions for the ICLR2018 conference are out! Congratulations to those who got their papers accepted, and I hope reviews serve as a source of inspiration for those who got their papers rejected. Now that we have the acceptance decisions and author names have been disclosed, let’s play with data...

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An early overview of ICLR2018 (part 2)

The rebuttal period has ended and final decisions will be notified by January 29th. In this post, differently from part one, I will provide updated information about the decision process. For those who just want the data right now, here is the browsable table with all the submissions under review:...

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An early overview of ICLR2018

Most reviews for ICLR2018 are out and given the success of the past edition it is time for the next one :) Update: I have published an overview of the decision process in part 2, and final decisions in part 3. The sixth edition of ICLR will be held in...

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GSOC2017: RNNs on tiny-dnn

Recurrent Neural Networks (RNNs) are now central to many applications, from speech recognition to Computer Vision. Some examples are Image captioning, Visual Question Answering (VQA), autonomous driving, and even Lip reading. During this Google Summer of Code, I have extended the tiny-dnn framework with an RNN API, thus making it...

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Regularizing CNNs with Locally Constrained Decorrelations (ICLR2017)

TL;DR We propose to locally decorrelate the feature weights of CNNs. When the proposed method, which we call OrthoReg, is used to regularize the 40 layers of Wide Residual Networks, we obtain state of the art results on CIFAR, and SVHN. Here is an example of the effects of our...

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An early overview of ICLR2017

Machine learning is accelerating, we have an idea and it is on arxiv the next day, NIPS2016 was bigger than ever and it is difficult to keep track of all the new interesting work. Given that this is the first time I submit to ICLR, and taking advantage from all...

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How to kill bash script children when crtl+c

Using a script to run multiple tasks in background can be very handy but it can also be anoying when we press crtl+c to interrupt and the background processes keep working. There are many approaches to solve this but I have found the cleanest one is to simply trap the...

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Can not set ViewportOut in nvidia-settings

After plugging the second monitor, I could not find the correct resolution in nvidia-settings and it was impossible to do it manually. After having to solve this problem for the second time, I post it here so to remember. Look at nvidia-settings for the name of the monitors (In my...

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torch.async-hdf5-reader

I decided to share this script I was using in order to accelerate the training of neural nets making them to gather data in parallel. So I wrote some tests to check it performs well its basic functions and commented the code a little bit. Dependencies It depends on the...

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Mac Book Pro randomly goes to sleep fix

Magnets can make your Mac to sleep. This was driving me mad since I always put it on a sleeve that closes with a magnet. Here is the solution page: Apple support

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matconv2caffe v0.1 released

Convert Matconvnet models to Caffe with matconv2caffe. There is already a script to import caffe models to matconvnet thanks to @vedaldi. However, we needed the oposite so I made a script that converts the .caffemodel and extracts a deplotment .prototxt model definition and the average image. Currently it only works...

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How I installed Caffe in OS X Yosemite

Update Last time I had to compile it was much easier by using Cmake. It was as easy as creating a build folder and executing (after installing the dependencies): cmake -D CMAKE_BUILD_TYPE=RELEASE -D WITH_CUDA=OFF -D CMAKE_INSTALL_PREFIX=$PWD .. Then compiling with: make -j Of course keep track of their webpage to...

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