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CRiSM Seminar

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Location: MS.03

Mikhail Malyutov (Northeastern University)

Context-free and Grammer-free Statistical Testing Identity of Styles

Our theory justifies our thorough statistical modification CCC of D.Khmelev's conditional compression based classification idea of 2001 and the 7 years of intensive applied statistical implementation of CCC for authorship attribution of literary works.

Homogeneity testing based on SCOT training with applications to the financial modeling and Statistical Quality Control are also in progress. Both approaches are desrcibed in a Springer monograph which appears shortly. Stochastic Context Tree (abbreviated as SCOT) is m-Markov Chain with every state of a spring independent of the symbols in its more remote past than the context of length determined by the preceding symbols of this state.

In all of our applications we uncover a complex sparse structure of memory in SCOT models that allows excellent discrimination power. In additiion, a straightforward estimation of the stationary distributio of SCOT gives insight into contexts crucial for discrimination between, say, different regimes of financial data or between styles of different authors of literary tests.

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