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Stochastic optimization naturally arises in machine learning.
A stochastic approximation method
Robbins, H · 1951
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Asymptotic distribution of stochastic approximation procedures
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Diffusion approximations
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On field calibration of an electronic nose for benzene estimation in an urban pollution monitoring scenario
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Numerical methods for ordinary differential equations: initial value problems
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Pegasos: Primal estimated sub-gradient solver for svm
Shalev-Shwartz, S · 2011
First efficient convergence for streaming k-pca: a global, gap-free, and near-optimal rate
Allen-Zhu, Z · 2016
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Matrix completion has no spurious local minimum
Ge, R · 2016
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Inference of high-dimensional autoregressive generalized linear models
Hall, E. C · 2016
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Streaming pca: Matching matrix bernstein and near-optimal finite sample guarantees for oja’s algorithm
Jain, P · 2016
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Symmetry, saddle points, and global geometry of nonconvex matrix factorization
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Stochastic block mirror descent methods for nonsmooth and stochastic optimization
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Escaping from saddle points—online stochastic gradient for tensor decomposition
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Complete dictionary recovery over the sphere
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Ergodic mirror descent
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Proximal stochastic methods for nonsmooth nonconvex finite-sum optimization
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A geometric analysis of phase retrieval
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Natasha 2: Faster non-convex optimization than sgd
Allen-Zhu, Z · 2017
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Online partial least square optimization: Dropping convexity for better efficiency and scalability
Chen, Z · 2017
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First-order methods almost always avoid saddle points
Lee, J. D · 2017
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