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Electronic Colloquium on Computational Complexity

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TR21-132 | 11th September 2021
Eric Binnendyk

Pseudo-random functions and uniform learnability

Revisions: 1

Boolean circuits are a model of computation. A class of Boolean circuits is called a polynomial class if the number of nodes is bounded by a polynomial function of the number of input variables. A class $C_n[s(n)]$ of Boolean functions is called learnable if there are algorithms that can approximate ... more >>>


TR21-131 | 10th September 2021
Olaf Beyersdorff, Benjamin Böhm

QCDCL with Cube Learning or Pure Literal Elimination - What is best?

Revisions: 1

Quantified conflict-driven clause learning (QCDCL) is one of the main approaches for solving quantified Boolean formulas (QBF). We formalise and investigate several versions of QCDCL that include cube learning and/or pure-literal elimination, and formally compare the resulting solving models via proof complexity techniques. Our results show that almost all of ... more >>>


TR21-130 | 7th September 2021
Srinivasan Arunachalam, João F. Doriguello

Matrix hypercontractivity, streaming algorithms and LDCs: the large alphabet case

Revisions: 1

Hypercontractive inequalities for real-valued functions over the Boolean cube play an important role in theoretical computer science. In this work, we prove a hypercontractive inequality for matrix-valued functions defined over large alphabets, generalizing the result of Ben-Aroya, Regev, de Wolf (FOCS'08) for the Boolean alphabet. To obtain our result we ... more >>>



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