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We study computational and statistical consequences of problem geometry in stochastic and online optimization.
A stochastic approximation method
H. Robbins and S. Monro · 1951
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Minimax theorems
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The Volume of Convex Bodies and Banach Space Geometry , volume 94 of Cambridge Tracts in Mathematics
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Numerical Linear Algebra
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Convergence of Probability Measures
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Mirror descent and nonlinear projected subgradient methods for convex optimization
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The robustness of the p p -norm algorithms
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On the generalization ability of on-line learning algorithms
N. Cesa-Bianchi, A. Conconi, and C. Gentile · 2004
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Prediction, Learning, and Games
N. Cesa-Bianchi and G. Lugosi · 2006
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Elements of Information Theory, Second Edition
T. M. Cover and J. A. Thomas · 2006
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Adaptive online gradient descent
P. L. Bartlett, E. Hazan, and A. Rakhlin · 2007
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Online Learning: Theory, Algorithms, and Applications
S. Shalev-Shwartz · 2007
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Robust stochastic approximation approach to stochastic programming
A. Nemirovski, A. Juditsky, G. Lan, and A. Shapiro · 2009
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Primal-dual subgradient methods for convex problems
Y. Nesterov · 2009
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Stochastic convex optimization
Information-theoretic lower bounds on the oracle complexity of convex optimization
A. Agarwal, P. L. Bartlett, P. Ravikumar, and M. J. Wainwright · 2012
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Online learning and online convex optimization
S. Shalev-Shwartz · 2012
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Optimal detection of sparse principal components in high dimension
Q. Berthet and P. Rigollet · 2013
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Estimation, optimization, and parallelism when data is sparse
J. C. Duchi, M. I. Jordan, and H. B. McMahan · 2013
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Gaussian Estimation: Sequence and Wavelet Models
I. Johnstone · 2017
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The marginal value of adaptive gradient methods in machine learning
A. C. Wilson, R. Roelofs, M. Stern, N. Srebro, and B. Recht · 2017
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Introduction to Nonparametric Estimation
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Lectures in geometric functional analysis
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Nemirovski’s inequalities revisited
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Reducibility and computational lower bounds for problems with planted sparse structure
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Black-box reductions for parameter-free online learning in Banach spaces
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Introductory lectures on stochastic convex optimization
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Scale-free online learning
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Matrix-free preconditioning in online learning
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Statistical and computational limits for sparse matrix detection
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