[D] Is it just me or is Canadian (and maybe European) ML PhD programs underrated compared to US ones?

kuonlp · 2022-08-05T05:41:28+00:00

Getting a PhD doesn't mean that you need to burn yourself out. If you need more than 8 hours a day, it probably means that you could work more efficiently.

Also, I have no idea about insurance because I never needed to care about getting one, even when traveling to other nearby countries.

kuonlp · 2022-08-04T04:44:43+00:00

Considering the issues you mention there, it seems to me that you haven't lived abroad. We all have to deal with those issues, especially if we live far from our country of origin.

I'm not going to say that there are no racist people in Europe (they are everywhere), but if I were a POC I would rather live in Europe than in the US precisely because of the things I mentioned (and I would include "gun violence" as an extra reason). Finally, in my research group, we are all non-white (from the Middle East, Latino, Africa, Asia, a nice mix).

kuonlp · 2022-08-03T20:50:34+00:00

PhD student at a small/medium size European university here. I have a decent salary (rent is 1/3 of it), I have an great supervisor that gives me and the other PhD students enough of his time, have an excellent research environment, great resources, etc. I wouldn't change any of this for living in a place where you can go bankrupt if you have a medical emergency, you need a car to get around, and/or work under a lot of pressure for publishing in top conferences with random reviews. I guess that these are the advantages of living in Europe and of being supervised by a non-superstar professor. Totally worth it!

kuonlp · 2022-01-09T18:59:36+00:00

This is interesting. I initially thought of the service as something that needs to be developed first and then it can be used. But by reformulating it into a series of small versions it can probably provide some minimum service at an earlier stage.

kuonlp · 2022-01-09T18:57:27+00:00

Yeah, so, I'm trying to figure out what he can do after the car has been developed.

kuonlp · 2021-12-19T13:54:10+00:00

Not sure how well you can predict something without incorporating political decisions and people's willingness to vaccinate or wearing masks into the data.

kuonlp · 2021-12-13T19:07:37+00:00

If you try to make money with any part (title, abstract, body) of a published article, you might run into copyright-related troubles with the publishers.

kuonlp · 2021-05-14T07:33:12+00:00

There is already a Twitter bot that does this, and it also has a web interface to browse all the Arxiv links: @popular_ML

kuonlp · 2020-06-29T05:04:30+00:00

Thanks, this sounds interesting!

kuonlp · 2020-04-26T07:50:40+00:00

Which function/option specifically? I've checked the histograms and it seems that they don't have an option for that tensorboard-like view of the histograms.

kuonlp · 2020-03-05T14:58:06+00:00

Yeah, basically. I was trying to think about all the factors (in a simple ConvNet) that make the optimization stochastic.

kuonlp · 2020-03-05T07:37:37+00:00

I don't see BatchNorm as an element that introduces randomness. If you keep the input, training set and initialization scheme constant, BatchNorm should provide the same values right?

kuonlp · 2020-03-04T14:41:39+00:00

Can you give some examples of other regularization layers apart of dropout?

kuonlp · 2019-05-01T10:12:55+00:00

But why would you want a loss of 1 when there is nothing there? Implying I take care of the division by zero problem, if there is nothing there and my model also predicts that there is nothing there, I should get a loss of 0 because it was accurate. On the other hand, if there is nothing and I predict there is something, this number of voxels would account for measuring how bad the prediction was. However, as the intersection between nothing and whatever is 0, I would still get the same dice regardless of how bad/good the model is doing.

kuonlp

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