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arxiv: 1409.3821 · v3 · pith:25ZW3U2Vnew · submitted 2014-09-12 · 📊 stat.CO · cs.IT· cs.LG· math.IT

Computational Implications of Reducing Data to Sufficient Statistics

Andrea Montanari This is my paper
classification 📊 stat.CO cs.ITcs.LGmath.IT
keywords datareducingstatisticssufficientestimationimplicationsadvantageousanalysis
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Given a large dataset and an estimation task, it is common to pre-process the data by reducing them to a set of sufficient statistics. This step is often regarded as straightforward and advantageous (in that it simplifies statistical analysis). I show that -on the contrary- reducing data to sufficient statistics can change a computationally tractable estimation problem into an intractable one. I discuss connections with recent work in theoretical computer science, and implications for some techniques to estimate graphical models.

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