Sublinear time algorithms for approximate semidefinite programming von Garber, Dan, Hazan, Elad

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Linear convergence of Frank–Wolfe for rank-one matrix recovery without strong convexity von Garber, Dan

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On the Convergence of Projected-Gradient Methods with Low-Rank Projections for Smooth Convex Minimization over Trace-Norm Balls and Related Problems von Garber, Dan

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A Linearly Convergent Variant of the Conditional Gradient Algorithm under Strong Convexity, with Applications to Online and Stochastic Optimization von Garber, Dan, Hazan, Elad

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Efficient Online Linear Optimization with Approximation Algorithms von Garber, Dan

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Low-rank extragradient methods for scalable semidefinite optimization von Garber, Dan, Kaplan, Atara

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On the Efficient Implementation of the Matrix Exponentiated Gradient Algorithm for Low-Rank Matrix Optimization von Garber, Dan, Kaplan, Atara

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Learning Optimal Forecast Aggregation in Partial Evidence Environments von Babichenko, Yakov, Garber, Dan

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Improved complexities of conditional gradient-type methods with applications to robust matrix recovery problems von Garber, Dan, Kaplan, Atara, Sabach, Shoham

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From Oja's Algorithm to the Multiplicative Weights Update Method with Applications von Garber, Dan

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Adaptive Universal Linear Filtering von Garber, D., Hazan, E.

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Low-Rank Extragradient Methods for Scalable Semidefinite Optimization von Kaplan, Dan Garber. Atara

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Projection-Free Online Convex Optimization with Time-Varying Constraints von Garber, Dan, Kretzu, Ben

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Efficiency of First-Order Methods for Low-Rank Tensor Recovery with the Tensor Nuclear Norm Under Strict Complementarity von Garber, Dan, Kaplan, Atara

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Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and Sparsity von Garber, Dan

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Projection-free Online Exp-concave Optimization von Garber, Dan, Kretzu, Ben

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On the Convergence of Stochastic Gradient Descent with Low-Rank Projections for Convex Low-Rank Matrix Problems von Garber, Dan

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Linear Convergence of Frank-Wolfe for Rank-One Matrix Recovery Without Strong Convexity von Garber, Dan

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From Oja's Algorithm to the Multiplicative Weights Update Method with Applications von Garber, Dan

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Low-Rank Mirror-Prox for Nonsmooth and Low-Rank Matrix Optimization Problems von Garber, Dan, Kaplan, Atara

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