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The Complexity of Making the Gradient Small in Stochastic Convex Optimization.
Dylan J. Foster
Ayush Sekhari
Ohad Shamir
Nathan Srebro
Karthik Sridharan
Blake E. Woodworth
Published in:
CoRR (2019)
Keyphrases
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convex optimization
interior point methods
low rank
primal dual
convex optimization problems
convex relaxation
total variation
computational complexity
worst case
norm minimization
convex constraints
augmented lagrangian
semidefinite program
semi definite programming
low rank matrix
operator splitting