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Electronic Colloquium on Computational Complexity

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TR21-174 | 29th November 2021
Tom Gur, Min-Hsiu Hsieh, Sathyawageeswar Subramanian

Sublinear quantum algorithms for estimating von Neumann entropy

Entropy is a fundamental property of both classical and quantum systems, spanning myriad theoretical and practical applications in physics and computer science. We study the problem of obtaining estimates to within a multiplicative factor $\gamma>1$ of the Shannon entropy of probability distributions and the von Neumann entropy of mixed quantum ... more >>>


TR21-173 | 5th December 2021
Ninad Rajgopal, Rahul Santhanam

On the Structure of Learnability beyond P/poly

Motivated by the goal of showing stronger structural results about the complexity of learning, we study the learnability of strong concept classes beyond P/poly, such as PSPACE/poly and EXP/poly. We show the following:

1. (Unconditional Lower Bounds for Learning) Building on [KKO13], we prove unconditionally that BPE/poly cannot be weakly ... more >>>


TR21-172 | 1st December 2021
Robert Andrews, Michael Forbes

Ideals, Determinants, and Straightening: Proving and Using Lower Bounds for Polynomial Ideals

We show that any nonzero polynomial in the ideal generated by the $r \times r$ minors of an $n \times n$ matrix $X$ can be used to efficiently approximate the determinant. Specifically, for any nonzero polynomial $f$ in this ideal, we construct a small depth-three $f$-oracle circuit that approximates the ... more >>>



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