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Shakir Mohamed

http://www.shakirm.com/publications.html

Research Scientist in Machine Learning and Artificial Intelligence. S Mohamed and D. J. Rezende, Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning. Neural Information Processing Systems (NIPS) 2015. D J Rezende and S. Mohamed, Variational Inference with Normalizing Flows. International Conference on Machine Learning (ICML), 2015. S Mohamed. A Statistical View of Deep Learning. Technical note, 2015. S Mohamed, A Tutorial on Variational Inference for Machine Learning.

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Shakir Mohamed

http://www.shakirm.com/bio.html

Research Scientist in Machine Learning and Artificial Intelligence. Paper on Semi-supervised learning with Deep generative models accepted at NIPS. Paper available. Speaking at ICML in the session on Deep Learning on Deep Generative Models. Paper on Stochastic backpropagation and Variational learning accepted at ICML. Speaking at Statlearn 2014, Paris on sparse Bayesian learning. Attending CIFAR Global Academy meeting in Banff, Canada. Giving a talk in Cambridge on adaptive HMC. In at the University of C...

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danielslater.net danielslater.net

DANIEL SLATER'S BLOG: Using Net2Net to speed up network training

http://www.danielslater.net/2016/05/using-net2net-to-speed-up-network.html

Thursday, May 26, 2016. Using Net2Net to speed up network training. When training neural networks there are 2 things that combine to make life frustrating:. Neural networks can take an insane amount of time of train. If a network could be trained quickly number 2 wouldn't really matter, we could just do a grid search(or even particle swarm optimization. Or maybe Bayesian optimization. The amount of time to train is counted in days so better hope your first guess was good. I have posted a numpy implementa...

danielslater.net danielslater.net

DANIEL SLATER'S BLOG: June 2015

http://www.danielslater.net/2015_06_01_archive.html

Thursday, June 18, 2015. Why there is a big unsupervised learning shaped whole in the universe. Unfortunately so far we are a long way from that and the technique shown here seems trivial compared to that goal. But the goal is interesting enough that it is worth pursuing. The answer to the question "what am I asking an unsupervised network to do? An example competitive learning neural net. It is also available in C#. From random import uniform class UnsupervisedNN(object): def init (self, size of input a...

danielslater.net danielslater.net

DANIEL SLATER'S BLOG: August 2015

http://www.danielslater.net/2015_08_01_archive.html

Saturday, August 29, 2015. Presenting WikiDataDotNet - Client API for WikiData. Is one of those things that sets the mind boggling at the possibilities of the internet. It's a project, started by the WikiMedia foundation, to collect structured data on everything. If you are doing anything related to machine learning, it is the best source of data I have so far found. Https:/ www.wikidata.org/w/api.php? This will return a JSON file with sections like:. Here we see the id of the item, in this case Q38.

danielslater.net danielslater.net

DANIEL SLATER'S BLOG: October 2015

http://www.danielslater.net/2015_10_01_archive.html

Tuesday, October 27, 2015. Even more quick summaries of research papers. Following on from part 1. Here are even more quick summaries of research papers,. Generative NeuroEvolution for DeepLearning. Uses the MNIST hand-drawn digits dataset, trains both a normal deep network and a convolutional network. HyperNEAT on it's own performs very badly. Using HyperNEAT to generate a number of layers and then backprop on the final layer is achieves 58.4% for normal ANNs. ES-HyperNeat uses the connection weights va...

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DANIEL SLATER'S BLOG: Deep-Q learning Pong with Tensorflow and PyGame

http://www.danielslater.net/2016/03/deep-q-learning-pong-with-tensorflow.html

Sunday, March 13, 2016. Deep-Q learning Pong with Tensorflow and PyGame. In a previous post. We went built a framework for running learning agents against PyGame. Now we'll try and build something in it that can learn to play Pong. We will be aided in this quest by two trusty friends Tensorflow. Google's recently released numerical computation library and this paper. On reinforcement learning for Atari games by Deepmind. Is a good starting point for learning. You will need Python 2 or 3 installed. In the...

danielslater.net danielslater.net

DANIEL SLATER'S BLOG: May 2016

http://www.danielslater.net/2016_05_01_archive.html

Thursday, May 26, 2016. Using Net2Net to speed up network training. When training neural networks there are 2 things that combine to make life frustrating:. Neural networks can take an insane amount of time of train. If a network could be trained quickly number 2 wouldn't really matter, we could just do a grid search(or even particle swarm optimization. Or maybe Bayesian optimization. The amount of time to train is counted in days so better hope your first guess was good. I have posted a numpy implementa...

danielslater.net danielslater.net

DANIEL SLATER'S BLOG: Mini-Pong and Half-Pong

http://www.danielslater.net/2016/05/mini-pong-and-half-pong.html

Monday, May 2, 2016. I'm going to be giving a talk/tutorial at PyDataLondon 2016. On Friday the 6th of may, if your in London that weekend I would recommend going, there are going to be lots of interesting talks, and if you do go please say hi. Possibly they are using other tricks not reported in the paper, or just lots of hyper parameter tuning, or there are still more bugs in my implementation(entirely possible, if anyone finds any please submit). Distance from building our future robot overlords, stil...

danielslater.net danielslater.net

DANIEL SLATER'S BLOG: November 2015

http://www.danielslater.net/2015_11_01_archive.html

Sunday, November 8, 2015. Quick summaries of research papers around dynamically generating network structure. I've been reading a lot of research papers on how the structure of ANN can be generated/detected. Here are some quick summaries of interesting papers in that area. Dynamic Node creation in backpropagation networks. Looks at attempting to find a good number of hidden nodes for a network by starting small and growing the correct number of hidden nodes. After training a standard ANN we can potential...

danielslater.net danielslater.net

DANIEL SLATER'S BLOG: PyDataLondon 2016

http://www.danielslater.net/2016/05/pydatalondon-2016.html

Sunday, May 15, 2016. Last week I gave a talk at PyDataLondon 2016. Hosted at the Bloomberg offices in central London. If you don't know anything about PyData. It is an community of Python data science enthusiasts that run various meetups and conferences across the world. If your interested in that sort of thing and they are running something near to you I would highly recommend checking it out. Below is the YouTube video for my talk and. Is the associated GitHub. Which includes all the example code.

danielslater.net danielslater.net

DANIEL SLATER'S BLOG: Particle Swarm Optimization in Python

http://www.danielslater.net/2015/12/particle-swarm-optimization-in-python.html

Saturday, December 5, 2015. Particle Swarm Optimization in Python. Is a short and sweet particle swarm optimization implementation in Python. For more information on particle swarm optimization check out Particle swarm optimization in F#. Example usage is like so:. Def simple error function(args): return args[0] args[1] number of parameters = 2 max iterations = 100 best parameters, best error score = particle swarm optimize(simple error function, number of parameters, max iterations).

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Shakir Mohamed

Research Scientist in Machine Learning and Artificial Intelligence. Research areas, code, data. Link to my blog. Paper on Semi-supervised learning with Deep generative models accepted at NIPS. Paper available. Speaking at ICML in the session on Deep Learning on Deep Generative Models. Paper on Stochastic backpropagation and Variational learning accepted at ICML. Paper available. I completed my PhD with Zoubin Ghahramani. At the University of Cambridge, where I was a Commonwealth Scholar to the United Kin...

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Web Design and Development. See how Shakir Multimedia can help you gain and keep more customers. From web design and development. And SEO, to photography, illustration and social media marketing, call us today for a full quotation. Social Media is everywhere. It cannot. Be ignored. And why should it? It's a fantastic way to get your message in. Front of thousands of potential. Customers on a regular basis and engage with them in real time. We offer Social Media services from. Work for your company? And Y...

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