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cambridge. org > core > journals > combinatorics-probability-and-computing > article > abs > trace-reconstruction-of-matrices-and-hypermatrices > 3 E88839 E10 D9 A783 FC379 B5 FABD5 A3 F1

Trace reconstruction of matrices and hypermatrices | Combinatorics, Probability and Computing

5+ hour, 52+ min ago  (324+ words) A trace of a sequence is generated by deleting each bit of the sequence independently with a fixed probability. The well-studied trace reconstruction problem asks how many traces are required to reconstruct an unknown binary sequence with high probability. In…...

Cambridge Core
cambridge. org > core > journals > advances-in-applied-probability > article > comparing-the-efficiency-of-general-state-space-reversible-mcmc-algorithms > 4 A5 C3 F1 CF00 F8 A65 F2803489393 B1 D9 B

Comparing the Efficiency of General State Space Reversible MCMC Algorithms | Advances in Applied Probability

2+ mon, 3+ week ago  (1762+ words) Published online by Cambridge University Press:" 15 January 2026 The advantage is that the Markov kernel P provides much simpler probability measures at each step, making it easier to compute, while the law of the Markov chain, $X_k$, approaches the probability distribution $\pi…...

Symbols: mcmc
cambridge. org
cambridge. org > core > journals > computational-humanities-research > article > retrieving-information-from-unstructured-historical-sources-using-large-language-models > 845 FDD146 FF8 A9283 A32 BFF0 C3160 F5 F

Retrieving information from unstructured historical sources using large language models - Cambridge University Press & Assessment

4+ mon, 2+ week ago  (513+ words) Published online by Cambridge University Press:" 02 December 2025 Our approach involved a three-step process that combined the strengths of traditional and newer extraction methods: 1. Optical character recognition: We used Azure AI Document Intelligence to convert scanned book images into raw text....

Symbols: llms