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Electronic Colloquium on Computational Complexity

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TR26-249 | 12th October 2026
Halley Goldberg, Mikito Nanashima, Igor Oliveira

Learning, Compression, and Meta-Complexity

The idea that learning is closely tied to compression has long served as both a powerful principle and,
at times, an informal analogy across machine learning and learning theory. Here we focus on settings in
which that intuition can be made mathematically precise, surveying formal connections among learning
algorithms, data ... more >>>


TR26-248 | 10th October 2026
Nikolai Chukhin

Breaking the Parity Barrier for Constant-Depth Circuits

A constant-depth circuit consists of AND and OR gates of unbounded fan-in, arranged in a constant number of layers, that read the input literals; for example, a depth-three circuit is an OR of CNFs or an AND of DNFs. The classical lower bound of HÃ¥stad (1989) states that every depth-$d$ ... more >>>


TR26-247 | 11th October 2026
Sankeerth Rao Karingula, Shachar Lovett

A simplified proof of polynomial improvements for 3SUM and APSP

We give a simplified proof of the polynomial improvements for integer 3SUM and all-pairs shortest paths (APSP) established by Alman and Vassilevska Williams, with weaker exponents. The central ingredient is selected-entry matrix multiplication: computing a prescribed set of entries of a product of dense rectangular matrices. Starting from Sch\"onhage's inner/outer-product ... more >>>



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