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Electronic Colloquium on Computational Complexity

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TR24-068 | 10th April 2024
Pravesh Kothari, Peter Manohar

Superpolynomial Lower Bounds for Smooth 3-LCCs and Sharp Bounds for Designs

We give improved lower bounds for binary $3$-query locally correctable codes (3-LCCs) $C \colon \{0,1\}^k \rightarrow \{0,1\}^n$. Specifically, we prove:

(1) If $C$ is a linear design 3-LCC, then $n \geq 2^{(1 - o(1))\sqrt{k} }$. A design 3-LCC has the additional property that the correcting sets for every ... more >>>


TR24-067 | 10th April 2024
Mi-Ying Huang, Xinyu Mao, Guangxu Yang, Jiapeng Zhang

Breaking Square-Root Loss Barriers via Min-Entropy

Information complexity is one of the most powerful tools to prove information-theoretical lower bounds, with broad applications in communication complexity and streaming algorithms. A core notion in information complexity analysis is the Shannon entropy. Though it has some convenient properties, such as chain rules, Shannon entropy still has inherent limitations. ... more >>>


TR24-066 | 29th March 2024
Siu On Chan, Hiu Tsun Ng, Sijin Peng

How Random CSPs Fool Hierarchies

Revisions: 2

Relaxations for the constraint satisfaction problem (CSP) include bounded width, linear program (LP), semidefinite program (SDP), afinfe integer program (AIP), and the combined LP+AIP of Brakensiek, Guruswami, Wrochna, and Živný (SICOMP 2020). Tightening relaxations systematically leads to hierarchies and stronger algorithms. For the LP+AIP hierarchy, a constant level lower bound ... more >>>



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