Ivan Pouzyrevsky

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We present an efficient algorithm to estimate large modified Kneser-Ney models including interpolation. Streaming and sorting enables the algorithm to scale to much larger models by using a fixed amount of RAM and variable amount of disk. Using one machine with 140 GB RAM for 2.8 days, we built an unpruned model on 126 billion tokens. Machine translation(More)
We consider the problem of sorting a sequence of n keys in a RAM-like environment where memory faults are possible. An algorithm is said to be δ-resilient if it can tolerate up to δ memory faults during its execution. A resilient sorting algorithm must produce a sequence where every pair of uncorrupted keys is ordered correctly. Finocchi, Grandoni, and(More)
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