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Testing properties of distributions over big domains
April 28 @ 11:00 am
We describe an emerging research direction regarding the complexity of testing global properties of discrete distributions, when given access to only a few samples from the distribution. Such properties might include testing if two distributions have small statistical distance, testing various independence properties, testing whether a distribution has a specific shape (such as monotone decreasing, k-modal, k-histogram, monotone hazard rate,…), and approximating the entropy. We describe bounds for such testing problems whose sample complexities are sublinear in the size of the support.