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ECCC
Electronic Colloquium on Computational Complexity

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TR26-054 | 9th April 2026
Noah Singer, Madhur Tulsiani, Santhoshini Velusamy

Optimal Single-Pass Streaming Lower Bounds for Approximating CSPs

For an arbitrary family of predicates $\mathcal{F} \subseteq \{0,1\}^{[q]^k}$ and any $\epsilon > 0$, we prove a single-pass, linear-space streaming lower bound against the gap promise problem of distinguishing instances of Max-CSP$({\mathcal{F}})$ with at most $\beta+\epsilon$ fraction of satisfiable constraints from instances of with at least $\gamma-\epsilon$ fraction of satisfiable ... more >>>


TR26-053 | 9th April 2026
Lance Fortnow

How Does Machine Learning Manage Complexity?

We provide a computational complexity lens to understand the power of machine learning models, particularly their ability to model complex systems.

Machine learning models are often trained on data drawn from sampleable or more complex distributions, a far wider range of distributions than just computable ones. By focusing ... more >>>


TR26-052 | 7th April 2026
Shuichi Hirahara, Mikito Nanashima

A Sharp Characterization of Pessiland

It is a long-standing open question whether the average-case hardness of NP implies the existence of a one-way function. The hypothetical world in which this does not hold is called Pessiland, which is the most pessimistic among Impagliazzo's five possible worlds. In this paper, we present the first "sharp" characterization ... more >>>



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