prajit

6 ms·

1.
by prajit 4y ago
> Or any co/startup doing "deep tech" in the area of Deep Learning. Send me a message, my email is in my profile.
2.
by prajit 10y ago
If you're interested in Sequence to Sequence tasks (e.g. neural machine translation or abstractive summarization) with small data, check out our recent paper from Google Brain tackling this problem (disclaimer, I'm the first autho
3.
by prajit 11y ago
Yes, there are two types of parallelism: model and data. Data parallelism is simply training the the model on multiple computers with different minibatches, and aggregating the gradients. Model parallelism is hosting different parts of the
4.
by prajit 11y ago
I implemented this system for the final project of my computer vision class. Couldn't get it to work by the deadline, but I'm very familiar with this paper. Happy to answer any questions.
5.
by prajit 12y ago
"There’s the famous observation that the value of a network grows as a function of the square of the number of nodes" The value of a network is measured as O(V^2), where V is the number of nodes (users) in the network. "and a
6.
by prajit 12y ago
A question about the actual slides: why don't they use unsupervised pretraining (i.e. Sparse Autoencoder) for predicting MNIST? Is it just to show that they don't need pretraining to achieve good results or is there something deep
7.
by prajit 12y ago
This is great. Thank you.
8.
D3.js Source Code Walkthrough Part 1(prajitr.github.io)
4 points by prajit 12y ago|0 comments
9.
by prajit 13y ago
This is not "first come, first serve", right?
10.
by prajit 13y ago
Type in the Konami Code and see what happens (up, up, down, down, left, right, left, right, b, a) - an Easter Egg!