Viewing profile — highd

... so how do API users enable 1hr caching? I haven't found a setting anywhere.

I'm fairly confident that the new reddit React implementation can be improved in performance by a factor of 3x to 10x. I would be interested to hear others who have good reason to …

How are you doing your train/test split?

If you think identifying a hypothetical back door in something as complex as a router is not a difficult process you are simply uninformed.

More like classic Bayes. Taleb's pop-sci came a few decades later.

Do you have any details on the experiment procedures? E.g. hardware, training time, loss curves? It is difficult to confidently reproduce research without at least some of these de…

If you released any of the software you are using to do this I would find it extremely interesting!

You can do Q-Learning with a transformer. You simply define the state space as the observation sequence. This is in fact natural to do in partially observed settings. So your disti…

TFP cites decision transformers. Just using a transformer does not bypass the credit assignment problem. Transformers are an architecture for solving sequence modeling problems, e.…

Can you provide some technical details on what you do? Do you divide the number of channels on each real layered network by 4? I don't see anything describing this in the paper.

Golem is solving exactly this problem.

It's actually using just one day's data (one point) to predict the next day's data, let alone predicting 5 days.

This model is showing predictions one day into the future. The "test set" plot is all predictions made with data from 1 day ago. The input sequences have size 1, so no recurrence i…

Most of the research in compressed sensing type applications now is focused on more sophisticated prior distributions than sparse/Laplacian. These more general bayesian approaches …

Not to mention that it appears they're comparing against networks of the same architecture. If you build your quaternion components with with same number types as your reals you ef…

Regarding this and previous discussions on this topic on HN, it seems to me that one of the primary motivating factors when constructing a new ranking system should be the possibil…

Bayesian optimization is often applied on problems where the cost of function evaluation greatly exceeds the cost of any posterior updates etc. In this case sample efficiency is th…

Investors that investigate companies, identify hidden problems and report on them to the public help enable more accurate price discovery. This wouldn't happen at all if they could…

This is a great example of where crypto would be useful. But it's not the same as paying for pizza.

Cash is cheaper for merchants, but people have only continued to use credit cards more. Further, if crypto becomes attractive from a cost perspective Visa will just be forced to br…

This is secondary to there being no benefit to the average user for transacting in crypto vs Visa. What incentive is there for an end user to use even a hypothetically optimal cryp…

Not to mention: > Data on blockchains is by default, unencrypted, especially data that needs to be validated by the nodes. Databases are unsecured by default -> databases are overh…

Compressing neural networks for inference is an entire subfield of work, with a number of effective approaches. It looks like the paper doesn't compare against any of them?

Apparently TCP is over too: https://trends.google.com/trends/explore?date=all&q=tcp

Please release it! There are a lot of applications for a differentiable renderer that's compatible with DNN libraries.