Garber, Dan

31 publications

COLT 2025 Blackwell’s Approachability with Approximation Algorithms Dan Garber, Massalha Mhna

ICML 2024 Projection-Free Online Convex Optimization with Time-Varying Constraints Dan Garber, Ben Kretzu

AISTATS 2023 Faster Projection-Free Augmented Lagrangian Methods via Weak Proximal Oracle Dan Garber, Tsur Livney, Shoham Sabach

COLT 2023 Projection-Free Online Exp-Concave Optimization Dan Garber, Ben Kretzu

NeurIPS 2022 Frank-Wolfe-Based Algorithms for Approximating Tyler's M-Estimator Lior Danon, Dan Garber

NeurIPS 2022 Local Linear Convergence of Gradient Methods for Subspace Optimization via Strict Complementarity Ron Fisher, Dan Garber

COLT 2022 New Projection-Free Algorithms for Online Convex Optimization with Adaptive Regret Guarantees Dan Garber, Ben Kretzu

AISTATS 2021 Revisiting Projection-Free Online Learning: The Strongly Convex Case Ben Kretzu, Dan Garber

COLT 2021 Frank-Wolfe with a Nearest Extreme Point Oracle Dan Garber, Noam Wolf

NeurIPS 2021 Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems Atara Kaplan, Dan Garber

AISTATS 2020 Improved Regret Bounds for Projection-Free Bandit Convex Optimization Dan Garber, Ben Kretzu

COLT 2020 On the Convergence of Stochastic Gradient Descent with Low-Rank Projections for Convex Low-Rank Matrix Problems Dan Garber

ICML 2020 Online Convex Optimization in the Random Order Model Dan Garber, Gal Korcia, Kfir Levy

NeurIPS 2020 Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and Sparsity Dan Garber

AISTATS 2019 Fast Stochastic Algorithms for Low-Rank and Nonsmooth Matrix Problems Dan Garber, Atara Kaplan

AISTATS 2019 Logarithmic Regret for Online Gradient Descent Beyond Strong Convexity Dan Garber

COLT 2019 On the Regret Minimization of Nonconvex Online Gradient Ascent for Online PCA Dan Garber

JMLR 2019 Stochastic Canonical Correlation Analysis Chao Gao, Dan Garber, Nathan Srebro, Jialei Wang, Weiran Wang

ALT 2018 Efficient Coordinate-Wise Leading Eigenvector Computation Jialei Wang, Weiran Wang, Dan Garber, Nathan Srebro

ICML 2017 Communication-Efficient Algorithms for Distributed Stochastic Principal Component Analysis Dan Garber, Ohad Shamir, Nathan Srebro

NeurIPS 2017 Efficient Online Linear Optimization with Approximation Algorithms Dan Garber

NeurIPS 2016 Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis Weiran Wang, Jialei Wang, Dan Garber, Dan Garber, Nati Srebro

NeurIPS 2016 Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis Weiran Wang, Jialei Wang, Dan Garber, Dan Garber, Nati Srebro

ICML 2016 Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber, Elad Hazan, Chi Jin, Sham, Cameron Musco, Praneeth Netrapalli, Aaron Sidford

NeurIPS 2016 Faster Projection-Free Convex Optimization over the Spectrahedron Dan Garber, Dan Garber

NeurIPS 2016 Faster Projection-Free Convex Optimization over the Spectrahedron Dan Garber, Dan Garber

NeurIPS 2016 Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes Dan Garber, Dan Garber, Ofer Meshi

NeurIPS 2016 Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes Dan Garber, Dan Garber, Ofer Meshi

ICML 2015 Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets Dan Garber, Elad Hazan

ICML 2015 Online Learning of Eigenvectors Dan Garber, Elad Hazan, Tengyu Ma

NeurIPS 2011 Approximating Semidefinite Programs in Sublinear Time Dan Garber, Elad Hazan