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Or Zamir

@OREAXEAX

Assistant Professor, department of Computer Science, Tel Aviv University @TelAvivUni
Formerly: @the_IAS, @Princeton
orz.am/ir Joined January 2024
191 Following 679 Followers 671 Posts

Latest posts 5

Or Zamir @OREAXEAX
Blum-Luby-Rubinfeld showed that matrix multiplication is as hard on a random input as it is in the WC. I give the first unconditional such reduction for matrix inversion; and conditional (on our trapdoor matrices) reductions for singularity, rank, and det.
arxiv.org/abs/2611.03058
arxiv.org Worst-Case to Average-Case Reductions for Basic Linear Algebra We study worst-case to average-case reductions for basic linear-algebraic problems over finite fields. A seminal work of Blum, Luby, and Rubinfeld established that any algorithm that successfully...
Or Zamir @OREAXEAX
What do I think makes more plausible fine-grained hardness conjectures? Problems for which we know absolutely no useful structural mechanism, and can hope there isn't any.
When we had non-trivial factoring algorithms, a poly quantum (or classical) one shouldn't be shocking.
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1 replies 0 reposts 8 likes 1.9K views View on X
Or Zamir @OREAXEAX
So what changes? Most works on exp-time algos are now obsolete (incl. some of my own), and much elegance in fine-grained complexity is lost. Many intermediate conjs still hold (eg, OV), but the slickness of "we have a central assumption that sounds like a strong NP!=P" is buried
2 replies 2 reposts 50 likes 5.1K views View on X
Or Zamir @OREAXEAX
To slightly calm down the external discourse: Breaking ETH does not directly imply anything about P vs NP, nor that every NP problem has a better algorithm; in fact, even for SAT (rather than k-SAT for a constant k) we still don't know if (2-eps)^n time is possible!