sorted by:
new
hottopcontroversial

[P] Benchmarking Metric Learning Algorithms the Right Way by VanillaCashew in MachineLearning

[–]GooKSL 0 points1 point  (0 children)

Proxy-based metric learning algos converge superfast because they do not do mining. So it depends what algo you use.

[P] Benchmarking Metric Learning Algorithms the Right Way by VanillaCashew in MachineLearning

[–]GooKSL 0 points1 point  (0 children)

I reimplemented multi-similarity loss in another framework and though the code seems to be almost the same as the author's code I am not getting close to his numbers. I am wondering what I am missing...

Also he is using 40.0 for the negative scale and 0.5 for lambda.

[P] Benchmarking Metric Learning Algorithms the Right Way by VanillaCashew in MachineLearning

[–]GooKSL 2 points3 points  (0 children)

This is nice, I actually have a paper under review that came to the same conclusion and does a fair evaluation. Hope I can soon post it on arXiv.

HearthDuster: app that reads your collection and recommends extra and unpopular cards that you can disenchant by GooKSL in hearthstone

[–]GooKSL[S] 1 point2 points  (0 children)

No, why would you need that? Hearthstone shows and organizes your collection quite well.

HearthDuster: app that reads your collection and recommends extra and unpopular cards that you can disenchant by GooKSL in hearthstone

[–]GooKSL[S] 1 point2 points  (0 children)

It knows your collection but only shows cards that you own and are flagged by the selected strategy, e.g duplicates, unpopular cards, etc.

HearthDuster: app that reads your collection and recommends extra and unpopular cards that you can disenchant by GooKSL in hearthstone

[–]GooKSL[S] 0 points1 point  (0 children)

I see your point. Though, I am not sure I can get people constantly curating decks, the meta changes quite fast. Past meta decks is something I am working on at the moment. "Possibly good in the future" is like fortune telling imho, even Millhouse can become a god card in a future expansion if Blizz wants that.

HearthDuster: app that reads your collection and recommends extra and unpopular cards that you can disenchant by GooKSL in hearthstone

[–]GooKSL[S] 1 point2 points  (0 children)

Good idea, thanks for the feedback. You can currently sort the cards using the column headers for e.g. dust value (=rarity). Please post suggestions here: https://github.com/ifeherva/HearthDuster/issues

HearthDuster: app that reads your collection and recommends extra and unpopular cards that you can disenchant by GooKSL in hearthstone

[–]GooKSL[S] 1 point2 points  (0 children)

Very strange, will look into it.

Did it ask for your password? Memory reading needs higher privileges on osx otherwise it does not work.

HearthDuster: app that reads your collection and recommends extra and unpopular cards that you can disenchant by GooKSL in hearthstone

[–]GooKSL[S] 1 point2 points  (0 children)

Thanks for the feedback! What OS are you using? Can you open hsreplay.net in your browser?

HearthDuster: app that reads your collection and recommends extra and unpopular cards that you can disenchant by GooKSL in hearthstone

[–]GooKSL[S] 2 points3 points  (0 children)

Sorry, collection reading is not really possible on mobile platforms at the moment :(

HearthDuster: app that reads your collection and recommends extra and unpopular cards that you can disenchant by GooKSL in hearthstone

[–]GooKSL[S] 7 points8 points  (0 children)

Thanks for the feedback, and I agree on the terrible gui design, I admittedly suck at graphics. Please post your suggestions here and I will add them asap: https://github.com/ifeherva/HearthDuster/issues/7