randomizedalgs
Joined 4 years ago
Karma
61
Submissions
21
Member since
Dec 13
Recent submissions
Comment · 19 days ago
Both can be true at once:
(1) AI agents are going rogue
(2) And labs are skipping security basics
Comment · 1 month ago
In theoretical computer science, at least, researchers plan their work to finish on three major deadlines a year (SODA, STOC, FOCS). STOC [1] is requiring all submissions to be uploaded to ArXiv before submission, and allows up to 5 submissions per author. I wonder if they'll change their policy or instead adopt an additional de-facto limit of two per submitter.
[1] STOC 2027 Call for Papers https://acm-stoc.org/stoc2027/stoc2027-cfp.html
Comment · 2 months ago
Even the experts on the problem being solved find the writeups nearly impossible to read.
Example: https://nitter.poast.org/henryquantum/status/208362369543662...
Seems like a disservice to the community that openai put so little effort into producing good writeups...
Comment · 3 months ago
After skimming some of the writeups, I'm surprised that the frontier internal model still writes just as poorly as Sol.
Maybe good AI paper writing is further away than I thought...
Comment · 9 months ago
I'm an active researcher in TCS. For me, AI has not been very helpful on technical things (or even technical writing), but has been super helpful for (1) literature reviews; (2) editing papers (e.g., changing a convention everywhere in the paper); and (3) generating Tikz figures/animations.
Comment · 1 year ago
For perspective, the CS programs in the NSF already have a two-submission limit per year [1].
Besides reducing the incentive to spam, this rule has had another positive effect: As a researcher without funding, you don't have to spend your whole year writing grants. You can, instead, spend your time on actual research.
With that said, NIH grants tend to me much more narrow than CS ones, and I imagine that it takes a lot more grants to keep a lab going...
[1] https://www.nsf.gov/funding/opportunities/computer-informati...
Comment · 1 year ago
For perspective, in the same time period, The number of employees at Google multiplied by five. I wouldn't be surprised if the growth of the software industry, at least, actually outpaced the increase in H-1B visas.
Comment · 1 year ago
For perspective, in the same time period, The number of employees at Google multiplied by five. It seems likely that the number of highly educated positions, in general, increased by quite a bit during that time.
Comment · 2 years ago
Cool paper!
As a small comment, this seems closely related to another recent paper: History-Independent Dynamic Partitioning: Operation-Order Privacy in Ordered Data Structures (PODS 2024, Best Paper).
I'm not sure how they compare, since neither paper seems to know about the other. And I'm also not sure which paper came first, since the geometric search paper does not seem to post a publication date.
Comment · 2 years ago
I don't think the claim is true in quite as much generality as the author claims. Some deterministic data structures use much more space than time, for example, the deterministic implementation of a Van Emde Boas tree.
Comment · 2 years ago
Maybe quotient filters?
Comment · 2 years ago
I think you may have a backwards. Libcuckoo, CLHT, and TBB are widely used high performance C/C++ DRAM hash tables. I think TBB is the hash table Intel maintains, if I remember right.
So the DRAM experiments are apples to apples. It's actually the PMEM experiments, I think, that are comparing a new hash table on a new technology to previous hash tables that weren't designed specifically for that technology.
Comment · 2 years ago
I think these are more-often called "cache oblivious" algorithms