nicklo

12 ms·

31.
by nicklo 10y ago
Hey HN! One of the organizers here- let me know if you have any questions!
32.
MIT 6.S191 Intro to Deep Learning(introtodeeplearning.com)
2 points by nicklo 10y ago|0 comments
33.
by nicklo 10y ago
This problem has already been solved with decent success using deep learning. See: https://homes.cs.washington.edu/~jxie/pdf/deep3d.pdf
34.
Vanishing Gradients and the Magic of LSTMs(harinisuresh.com)
2 points by nicklo 10y ago|0 comments
35.
TensorFlow Crash Course(nicklocascio.com)
3 points by nicklo 10y ago|0 comments
36.
by nicklo 10y ago
Would be super cool if someone applied deep generative models to synthesize new natural images from input drawings using this dataset.
37.
by nicklo 10y ago
Deep image captioning is essentially what you are describing. Check out: http://cs.stanford.edu/people/karpathy/deepimagesent/ http://cs.stanford.edu/people/karpathy/densecap/
38.
by nicklo 10y ago
I use a plain pdf resume that is written in Latex. I host it on Overleaf so its always easy to update. http://nicklocascio.com/resume.pdf
39.
by nicklo 10y ago
It absolutely is. DeepMind reported that 1 second of audio generation takes about 90 minutes to generate.
40.
by nicklo 10y ago
Super cool stuff in this paper. At its heart, this is a new training architecture that allows parameter weights to be updated faster in a distributed setting. The speed-up happens like so: instead of waiting for the full error gradient to p
41.
by nicklo 10y ago
This comment is mind-numbingly anecdotal and runs wildly contrary to reality. '"Happiness" at Mt Holyoke' - here's the list of majors at Mt Holyoke: https://www.mtholyoke.edu/acad/majors . &#x27
42.
by nicklo 10y ago
Yeah their work is very cool! The two tasks are a bit different however. Their system is for the task of generating regular expressions given a set of positive and negative examples of what the regex should match. It uses genetic algorithms
43.
by nicklo 10y ago
Thanks! Starting this work, we realized that large regex datasets (large enough to apply deep-learning to) were difficult to come by. So we came up with a methodology that allowed us to make a pretty decent-sized dataset for cheap. We are g
44.
by nicklo 10y ago
Sure! Some positive ones: 1) Spot-on prediction: PROMPT: lines with 3 or more characters or lower-case letters PRED: ((.)|([a-z])){3,} GOLD: ((.)|([a-z])){3,} 2) Learned to generalize and produced a simpler regex: PROMPT: l
45.
by nicklo 10y ago
Hey HN! One of the authors here. This was a fun project to work on. Happy to answer any questions :) Code + data here: https://github.com/nicholaslocascio/deep-regex
46.
DeepRegex: Neural Generation of Regular Expressions from Natural Language(arxiv.org)
145 points by nicklo 10y ago|21 comments
47.
by nicklo 10y ago
That account (bertilda-lovejoy) was made 10 minutes ago, so don't get too bent out of shape over it. Its likely a mens-rights red-pill-er intentionally misrepresenting feminist values by taking them to a tone-deaf extreme in a repo tha
48.
by nicklo 10y ago
Thanks for clearing that bit up. Glad that dietary considerations were made :)
49.
by nicklo 10y ago
Do you not find it unethical to serve your in-laws fake meat without informing them? Wouldn't you be upset if your in-laws served you seitan that was actually chicken? *edit: I bring this up because many people do not react well to mea
50.
by nicklo 10y ago
Hold up, an attempt to rectify systemic injustice is not reverse racism. YC's doing a great thing here to support and foster underrepresented groups in the startup founder world. Being from an underrepresented group makes so many thing
51.
Neural Artistic Style Transfer for Videos(youtube.com)
2 points by nicklo 10y ago|0 comments
52.
Deep Networks with Stochastic Depth(arxiv.org)
70 points by nicklo 11y ago|8 comments
53.
by nicklo 11y ago
The same way anyone gets good at anything - practice it. This may sound crazy but don't write it off. Go into bed during the day for 1 minute and don't fall asleep. Set an alarm and when it goes off, get out of bed. Repeat 5-10 ti
54.
by nicklo 11y ago
There are tons of ways to evaluate word vector quality! Word analogy tasks, word similarity tasks, contextual prediction tasks, etc. This link contains a bunch of relevant evaluation datasets and benchmarks obtained using word2vec, GloVe, e
55.
by nicklo 11y ago
MetaMind papers are always pretty awesome. Couple of great highlights from this paper: The visual saliency maps in Figure 6 are astounding and make their performance on this task even more impressive as they give a lot of insight into what
56.
by nicklo 11y ago
Wonderful write-up. Posts like these give just the right amount of detail and high-level insight. I especially appreciated the linear flow of the approaches section. The successes and roadblocks presented provide useful context into why cer
57.
Image QA using Convolutional Neural Network with Dynamic Parameter Prediction(gitxiv.com)
2 points by nicklo 11y ago|0 comments
58.
by nicklo 11y ago
From a technical standpoint, the paper is somewhat lacking. It's a standard Markov-chain generator with an additional prior defined on the cohesiveness of the generated text. I'm guessing all the press is due to it being US electi
59.
by nicklo 11y ago
Cool! Let me know if you run into any issues.
60.
by nicklo 11y ago
Thank you for this. I see now how my wording was unclear, but this is exactly what I had meant. Sorry for the confusing word choice.

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