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Classic Papers: Articles That Have Stood the Test of Time

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Re: Classic Papers: Articles That Have Stood the Test of Time

#41

Post by ferdterguson »

logicallee wrote: post #13

Out of curiosity, does anyone have any examples of scientific books (or papers) that are the exact opposite: influential or famous at the time but completely and utterly destroyed by the test of time. Like, that seem silly to us in how completely and utterly wrong they turned out to be in their every single conclusion. I'm thinking about research versions of Lord Kevin's favorite edict: "Heavier than air flying machi…

Not a field, but a person who everyone thought was Nobel prize bound and it turned out to be all BS. You may think that it's just one person, but the amount of research dollars that got allocated to try and prove or disprove all of this work would be staggering. https://en.wikipedia.org/wiki/Schön_scandal

Re: Classic Papers: Articles That Have Stood the Test of Time

#42

Post by ivansavz »

For everyone disappointed to see papers only from 2006, here is a consolation prize. Creating a Computer Science Canon: a Course of “Classic” Readings in Computer Science: http://l3d.cs.colorado.edu/~ctg/pubs/sigcsecanon.pdf (CS only, date range = [1806:2006])

Re: Classic Papers: Articles That Have Stood the Test of Time

#44

Post by drfuchs »

jventura wrote: post #35
drfuchs wrote: post #23

They completely missed, with 1800+ citations, the winner of the “Theory of Cryptography Conference (TCC) 2016 Test of Time award ”: “Calibrating Noise to Sensitivity in Private Data Analysis” by Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith. Oh, it also just won the 2017 Gödel Prize; it really ought to be at the top of both the “Theoretical Computer Science” and “Computer Security and Cryptography” list…

From the article: "This release of classic papers consists of articles that were published in 2006..". Your second one could be there (I haven't looked for it), but you're mentioning some problems with the article, maybe it's that..

They were both published in 2006, so not sure what you're getting at.

Google Scholar and Sean Henderson are promulgating a false historical record, and there seems to be no way to inform them so that they may correct themselves, other than whining here on HN and hoping they notice. Anybody have any other suggestions?

Re: Classic Papers: Articles That Have Stood the Test of Time

#47

Post by mindcrime »

Houshalter wrote: post #30
logicallee wrote: post #13

Out of curiosity, does anyone have any examples of scientific books (or papers) that are the exact opposite: influential or famous at the time but completely and utterly destroyed by the test of time. Like, that seem silly to us in how completely and utterly wrong they turned out to be in their every single conclusion. I'm thinking about research versions of Lord Kevin's favorite edict: "Heavier than air flying machi…

Sure fields of research go obsolete all the time. E.g. much of the computer vision stuff from 2006 is basically dead now. If you go further back, a lot of early AI research was exciting at the time, but is entirely forgotten about now.

If you go further back, a lot of early AI research was exciting at the time, but is entirely forgotten about now.

Interesting that you would use that example. I suspect, although I can't prove, that this is largely a mistake. Or maybe not so much a mistake as a choice that will wind up being revisited. That is, I think there is still a lot of "meat on the bone" for many of the AI techniques that were being explored in the 70's and 80's, and we will see another round of things suddenly coming back into favor at some point. It's happened before... remember when ANN's were completely out of vogue, and the computing power and data availability caused a sudden resurgence in interest in those? I would not be surprised to see similar things happening w/r/t various aspects of GOFAI.

More likely, I think we'll see additional integration / hybridization of probabilistic / pattern matching systems (using ANN's / Deep Learning / etc.) and symbolic processing and automated reasoning.

'course, I might be totally wrong, but that's my feeling ATM.

Re: Classic Papers: Articles That Have Stood the Test of Time

#48

Post by frankmcsherry »

drfuchs wrote: post #44
jventura wrote: post #35

Earlier quoted context omitted.

From the article: "This release of classic papers consists of articles that were published in 2006..". Your second one could be there (I haven't looked for it), but you're mentioning some problems with the article, maybe it's that..

They were both published in 2006, so not sure what you're getting at. Google Scholar and Sean Henderson are promulgating a false historical record, and there seems to be no way to inform them so that they may correct themselves, other than whining here on HN and hoping they notice. Anybody have any other suggestions?

https://support.google.com/scholar/contact/general

Re: Classic Papers: Articles That Have Stood the Test of Time

#49

Post by drfuchs »

frankmcsherry wrote: post #48
drfuchs wrote: post #44

Earlier quoted context omitted.

They were both published in 2006, so not sure what you're getting at. Google Scholar and Sean Henderson are promulgating a false historical record, and there seems to be no way to inform them so that they may correct themselves, other than whining here on HN and hoping they notice. Anybody have any other suggestions?

https://support.google.com/scholar/contact/general

(Frank?! Congratulations!) Yeah, that's a black hole, at least as of some time ago. But, in your honor, I'll try it again.
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