arXiv Machine Learning By Lunjia Hu, Salil Vadhan

Generalized and Unified Equivalences between Hardness and Pseudoentropy

Read the original on arXiv Machine Learning →

arXiv:2507. 05972v3 Announce Type: replace-cross Abstract: Pseudoentropy characterizations give quantitatively precise formulations of the relationship between computational hardness and computational randomness.

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arXiv Machine Learning
Aug 5

Quality Control Algorithms for Pattern Counting

arXiv:2608. 03439v1 Announce Type: cross Abstract: In recent work, Marcussen, Rubinfeld, and Sudan introduced the notion of quality control problems, which aim to capture the task of determining if a given input is truly random.

By Cassandra Marcussen, Ronitt Rubinfeld, Madhu Sudan
Hugging Face Trending Papers
Aug 3

Optimal Unambiguous DNFs and Alon-Saks-Seymour

We construct unambiguous DNFs having width $O(n)$ but $0$-certificate complexity $Ω(n^2)$. By utilizing the special structure of these DNFs, we prove a lifting theorem with a constant-sized gadget that lifts the DNF to a communication problem, while losslessly translating the separation in certificate complexity to a separation in communication complexity.