The Fast Convergence of Incremental PCA
نویسندگان
چکیده
We consider a situation in which we see samples Xn ∈ R drawn i.i.d. from somedistribution with mean zero and unknown covariance A. We wish to compute thetop eigenvector of A in an incremental fashion with an algorithm that maintainsan estimate of the top eigenvector in O(d) space, and incrementally adjusts theestimate with each new data point that arrives. Two classical such schemes aredue to Krasulina (1969) and Oja (1983). We give finite-sample convergence ratesfor both.
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