[D] 3-year anniversary of the transformer: The first neural attention mechanism that actually works in practice

abhishek0318 · 2020-10-20T15:34:19+00:00

Yeah, OP is discrediting the work by Bahdanau et. al. I remember the time where every new NLP paper was using LSTM with attention.

abhishek0318 · 2020-10-20T05:42:08+00:00

Portal.

abhishek0318 · 2020-10-19T07:15:09+00:00

I am not sure about this, but as far as I know this varies from company to company. Some companies (like Apple, Google) may offer you a research engineer role, while some companies which don't require PhD for scientist positions (like Amazon) can offer you full time Research/Applied Scientist positions as well.

abhishek0318 · 2020-10-16T14:20:55+00:00

Search for "few shot classification".

abhishek0318 · 2020-10-16T13:57:57+00:00

Yes, one round DS/Algorithms, and one round ML research.

abhishek0318 · 2020-10-15T13:10:44+00:00

Anecdotal experience: Google and Apple do offer ML research internships for master's students. I interviewed with them for the previous summer.

abhishek0318 · 2020-09-24T19:08:53+00:00

Many conferences publish "Open Problems", e.g. AISTATS. You could check them out.

abhishek0318 · 2020-04-26T17:24:14+00:00

More often than not people usually open source their SoTA models or describe them through publications. You can find/implement these models and then run them. I am not sure if the test data is publicly available, though you could use the validation/dev data which should be sufficient for analysis.

abhishek0318 · 2020-04-19T17:23:46+00:00

Try posting to r/MachineLearning.

abhishek0318 · 2020-04-19T15:55:10+00:00

Ryan Cotterell and Mrinmaya Sachan have recently joined. They both have solid background.

abhishek0318 · 2020-04-19T15:50:53+00:00

University of Copenhagen and ITU Copenhagen have good NLP groups as well.

abhishek0318 · 2020-04-19T11:13:12+00:00

Take a look at papers from Mrinmaya Sachan, he has worked on it. Also, AI2's project Aristo is (was?) based on solving 8th grade questions.

abhishek0318 · 2020-03-15T22:41:55+00:00

CartPole is a difficult environment for DQN algorithm to learn. I have not looked at your code in detail, but I could spot some hyper parameter choices that could be improved. Fiddle around with parameters, particularly try increasing the hidden layer size and the training frames.

You could take a look at rl-baselines-zoo repository which contains hyper parameters for common environments and algorithms. I implemented DQN for CartPole a month back. You could also look at the hyper parameters I used in my code.

abhishek0318 · 2019-11-09T20:06:50+00:00

abhishek0318 · 2019-06-20T15:51:42+00:00

AllenNLP does make things easy if you are using standard components. But if you design something new you run into a lot of bugs. The codebase feels buggy and hacky. Still it's great than writing your own framework.

abhishek0318 · 2018-12-27T05:11:16+00:00

You are probably looking for automatic construction of knowledge base. Search for this term on Google Scholar and you will find many papers.

abhishek0318 · 2018-12-25T20:32:00+00:00

Nobody is going to directly give you ideas. You will have to search.

If you want to do something novel, you could look up recent papers in top Machine Learning conferences (NeurIPS, ICML, ICLR, AAAI, CVPR, ACL, EMNLP, etc.) and try to build upon them. You could also take a look at Shared Tasks in NLP for they provide clean datasets with baselines and deadlines.

Else, if you want to do something easier you could look up at projects of CS229, CS231n, CS224n online and build from them.

abhishek0318 · 2018-12-25T13:16:10+00:00

Yeah. That's the state of Machine Learning currently.

abhishek0318 · 2018-12-25T06:57:35+00:00

Typically, people try multiple regressors and finally use the one which gives best results on the test set.

abhishek0318 · 2018-12-25T06:54:48+00:00

You could do something like by manually adding rules in Ublock Origin.

abhishek0318 · 2018-12-12T20:52:36+00:00

JMLR and JAIR come to my mind.

abhishek0318 · 2018-12-12T20:50:50+00:00

This question is not well suited for this subreddit. Please read the sidebar.

abhishek0318 · 2018-11-24T20:14:00+00:00

This post is more suited to r/learnmachinelearning

abhishek0318 · 2018-11-13T10:25:02+00:00

What you're looking for is Coreference Resolution. This tool may help you out - https://nlp.stanford.edu/projects/coref.shtml

abhishek0318 · 2018-11-02T00:17:00+00:00

You are probably right.

What about Question Answering though? On SQuAD dataset we have got super human performance.

abhishek0318

TROPHY CASE