63 citations · 66 across the 4 of their papers we have counts for
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math.OC2023
Stochastic Scale Invariant Power Iteration for KL-divergence Nonnegative Matrix Factorization
Cheolmin Kim, Youngseok Kim, Diego Klabjan
We introduce a mini-batch stochastic variance-reduced algorithm to solve finite-sum scale invariant problems which cover several examples in machine learning and statistics such as…
math.OC2019★ 1 cited
Scale Invariant Power Iteration
Cheolmin Kim, Youngseok Kim, Diego Klabjan
Power iteration has been generalized to solve many interesting problems in machine learning and statistics. Despite its striking success, theoretical understanding of when and how…
math.OC2019★ 2 cited
Stochastic Variance-Reduced Heavy Ball Power Iteration
Cheolmin Kim, Diego Klabjan
We present a stochastic variance-reduced heavy ball power iteration algorithm for solving PCA and provide a convergence analysis for it. The algorithm is an extension of heavy ball…