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math.NA2017★ 9 cited
Efficient coordinate-wise leading eigenvector computation
Jialei Wang, Weiran Wang, Dan Garber +1
We develop and analyze efficient "coordinate-wise" methods for finding the leading eigenvector, where each step involves only a vector-vector product. We establish global convergen…
math.NA2013★ 31 cited
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm
Deanna Needell, Nathan Srebro, Rachel Ward
We obtain an improved finite-sample guarantee on the linear convergence of stochastic gradient descent for smooth and strongly convex objectives, improving from a quadratic depende…