A well-recognized limitation of research on supervised sentence compression is the dearth of available training data. We propose a new and bountiful resource for such training data, which we obtain by mining the revision history of Wikipedia for sentence compressions and expansions. Using only a fraction of the available Wikipedia data, we have collected a training corpus of over 380,000 senten...

Considering a small image region and specifying a joint probability distribution which describes the likelihood of nding a speciic pattern in this image region, arithmetic coding can provide an optimum code that reaches the Shannon limit for the given probability distribution. Data compression is thus reduced to estimating joint probability distributions of patterns. This paper demonstrates how...

Storage-efficient privacy-preserving learning is crucial due to increasing amounts of sensitive user data required for modern tasks. We propose a framework reducing the storage cost while at same time providing privacy guarantees, without essential loss in utility learning. Our method comprises noise injection followed by lossy compression. show that, when appropriately matching compression dis...

A recent study proposes a metric to quantify how much information different types of epidemiological surveillance data, such as case counts and death counts, convey about the real-time transmission an epidemic.

This note proposes an algorithm for identifying the poles and residues of a meromorphic function from its noisy values on imaginary axis. The uses Möbius transform Prony’s method in frequency domain. Numerical results are provided to demonstrate performance algorithm.