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Electronic Colloquium on Computational Complexity

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REPORTS > 2022:
All reports in year 2022:
TR22-009 | 17th January 2022
C. Ramya, Anamay Tengse

On Finer Separations between Subclasses of Read-once Oblivious ABPs

Read-once Oblivious Algebraic Branching Programs (ROABPs) compute polynomials as products of univariate polynomials that have matrices as coefficients. In an attempt to understand the landscape of algebraic complexity classes surrounding ROABPs, we study classes of ROABPs based on the algebraic structure of these coefficient matrices. We study connections between polynomials ... more >>>

TR22-008 | 14th January 2022
Gil Cohen, Dean Doron, Ori Sberlo

Approximating Large Powers of Stochastic Matrices in Small Space

We give a deterministic space-efficient algorithm for approximating powers of stochastic matrices. On input a $w \times w$ stochastic matrix $A$, our algorithm approximates $A^{n}$ in space $\widetilde{O}(\log n + \sqrt{\log n}\cdot \log w)$ to within high accuracy. This improves upon the seminal work by Saks and Zhou (FOCS'95), that ... more >>>

TR22-007 | 14th January 2022
Halley Goldberg, Valentine Kabanets

A Simpler Proof of the Worst-Case to Average-Case Reduction for Polynomial Hierarchy via Symmetry of Information

We give a simplified proof of Hirahara's STOC'21 result showing that $DistPH \subseteq AvgP$ would imply $PH \subseteq DTIME[2^{O(n/\log n)}]$. The argument relies on a proof of the new result: Symmetry of Information for time-bounded Kolmogorov complexity under the assumption that $NP$ is easy on average, which is interesting in ... more >>>

TR22-006 | 12th January 2022
Benny Applebaum, Amos Beimel, Oded Nir, Naty Peter, Toniann Pitassi

Secret Sharing, Slice Formulas, and Monotone Real Circuits

A secret-sharing scheme allows to distribute a secret $s$ among $n$ parties such that only some predefined ``authorized'' sets of parties can reconstruct the secret, and all other ``unauthorized'' sets learn nothing about $s$. For over 30 years, it was known that any (monotone) collection of authorized sets can be ... more >>>

TR22-005 | 11th January 2022
Anup Rao

Sunflowers: from soil to oil

A \emph{sunflower} is a collection of sets whose pairwise intersections are identical. In this article, we shall go sunflower-picking. We find sunflowers in several seemingly unrelated fields, before turning to discuss recent progress on the famous sunflower conjecture of Erd\H{o}s and Rado, made by Alweiss, Lovett, Wu and Zhang.

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TR22-004 | 3rd January 2022
Silas Richelson, Sourya Roy

Analyzing Ta-Shma’s Code via the Expander Mixing Lemma

Random walks in expander graphs and their various derandomizations (e.g., replacement/zigzag product) are invaluable tools from pseudorandomness. Recently, Ta-Shma used s-wide replacement walks in his breakthrough construction of a binary linear code almost matching the Gilbert-Varshamov bound (STOC 2017). Ta-Shma’s original analysis was entirely linear algebraic, and subsequent developments have ... more >>>

TR22-003 | 4th January 2022
Noah Fleming, Stefan Grosser, Mika Göös, Robert Robere

On Semi-Algebraic Proofs and Algorithms

We give a new characterization of the Sherali-Adams proof system, showing that there is a degree-$d$ Sherali-Adams refutation of an unsatisfiable CNF formula $C$ if and only if there is an $\varepsilon > 0$ and a degree-$d$ conical junta $J$ such that $viol_C(x) - \varepsilon = J$, where $viol_C(x)$ counts ... more >>>

TR22-002 | 11th December 2021
Sravanthi Chede, Anil Shukla

Extending Merge Resolution to a Family of Proof Systems

Merge Resolution (MRes [Beyersdorff et al. J. Autom. Reason.'2021]) is a recently introduced proof system for false QBFs. Unlike other known QBF proof systems, it builds winning strategies for the universal player within the proofs. Every line of this proof system consists of existential clauses along with countermodels. MRes stores ... more >>>

TR22-001 | 28th December 2021
Yogesh Dahiya, Meena Mahajan

On (Simple) Decision Tree Rank

In the decision tree computation model for Boolean functions, the depth corresponds to query complexity, and size corresponds to storage space. The depth measure is the most well-studied one, and is known to be polynomially related to several non-computational complexity measures of functions such as certificate complexity. The size measure ... more >>>

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