Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
Data trusts could allay our privacy fears
Originally appeared as an Op-Ed in the Guardian Media and Tech Network.
Generating Large Images from Latent Vectors - Part Two
June 2, 2016
Deep Learning Trends @ ICLR 2016
### Deep Learning Trends @ ICLR 2016
Bayesian Deep Learning
Current trends in Machine Learning¶
TensorFlow Implementation of "A Neural Algorithm of Artistic Style"
This notebook and code are available on Github.
Deep Reinforcement Learning： Pong from Pixels
This is a long overdue blog post on Reinforcement Learning (RL). RL is hot! You may have noticed that computers can now automatically learn to play ATARI games (from raw game pixels!), they are beating world champions at Go, simulated quadrupeds are learning to run and leap, and robots are learning how to perform complex manipulation tasks that defy explicit programming. It turns out that all of these advances fall under the umbrella of RL research. I also became interested in RL myself over the last ~year: I worked through Richard Sutton’s book, read through David Silver’s course, watched John Schulmann’s lectures, wrote an RL library in Javascript, over the summer interned at DeepMind working in the DeepRL group, and most recently pitched in a little with the design/development of OpenAI Gym, a new RL benchmarking toolkit. So I’ve certainly been on this funwagon for at least a year but until now I haven’t gotten around to writing up a short post on why RL is a big deal, what it’s about, how it all developed and where it might be going.
Becoming a Data Scientist Podcast Episode 11： Stephanie Rivera
Podcast Audio Links:Link to podcast Episode 11 audioPodcast’s RSS feed for podcast subscription appsPodcast on StitcherPodcast on iTunes
Assorted links
Star Wars - Episode V “The Empire Strikes Back” Homage (Title Sequence) from KROFL on Vimeo.
Concurrent bloom filters
Bloom filters are probabilistic data structure for determining whether an element is in a set. Such a data structure offers only two methods - add and mightContain. Google’s guava library offers a nice implementation, but unfortunately this implementation (like every implementation I’ve found) is not concurrent. Concurrent reads are no problem, but writes are trickier - and reading while writing is also not straightforward.