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Found 5 papers, 0 papers with code
Hardness of Learning Boolean Functions from Label Proportions
This is in contrast with the work of (Saket, NeurIPS'21) which gave a $(2/5)$-approximation for learning ORs using a halfspace.
Outlier Robust Multivariate Polynomial Regression
Furthermore, we show that it is possible to have the run-time be independent of $1/\sigma$, at the cost of a higher sample complexity.
Conditional Dichotomy of Boolean Ordered Promise CSPs
Assuming the Rich 2-to-1 Conjecture, we prove that a Boolean Ordered PCSP can be solved in polynomial time if for every $\epsilon>0$, it has polymorphisms where each coordinate has Shapley value at most $\epsilon$, else it is NP-hard.
Computational Complexity Logic in Computer Science
Improved Maximally Recoverable LRCs using Skew Polynomials
Such an LRC is Maximally Recoverable (MR), if it offers the best blend of locality and global erasure resilience -- namely it can correct all erasure patterns whose recovery is information-theoretically feasible given the locality structure (these are precisely patterns with up to `$a$' erasures in each local group and an additional $h$ erasures anywhere in the codeword).
Information Theory Computational Complexity Information Theory Rings and Algebras
AC-DC: Amplification Curve Diagnostics for Covid-19 Group Testing
The first part of the paper presents a review of the gold-standard testing protocol for Covid-19, real-time, reverse transcriptase PCR, and its properties and associated measurement data such as amplification curves that can guide the development of appropriate and accurate adaptive group testing protocols.
