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Electronic Colloquium on Computational Complexity

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TR17-017 | 5th February 2017
Michal Moshkovitz, Dana Moshkovitz

Mixing Implies Lower Bounds for Space Bounded Learning

One can learn any hypothesis class $H$ with $O(\log|H|)$ labeled examples. Alas, learning with so few examples requires saving the examples in memory, and this requires $|X|^{O(\log|H|)}$ memory states, where $X$ is the set of all labeled examples. A question that arises is how many labeled examples are needed in ... more >>>


TR17-016 | 31st January 2017
Vishwas Bhargava, Gábor Ivanyos, Rajat Mittal, Nitin Saxena

Irreducibility and deterministic r-th root finding over finite fields

Constructing $r$-th nonresidue over a finite field is a fundamental computational problem. A related problem is to construct an irreducible polynomial of degree $r^e$ (where $r$ is a prime) over a given finite field $\F_q$ of characteristic $p$ (equivalently, constructing the bigger field $\F_{q^{r^e}}$). Both these problems have famous randomized ... more >>>


TR17-015 | 4th February 2017
Ilan Komargodski, Moni Naor, Eylon Yogev

White-Box vs. Black-Box Complexity of Search Problems: Ramsey and Graph Property Testing

Revisions: 2

Ramsey theory assures us that in any graph there is a clique or independent set of a certain size, roughly logarithmic in the graph size. But how difficult is it to find the clique or independent set? If the graph is given explicitly, then it is possible to do so ... more >>>



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