Dan Garber - RankMe

81 papers A* 18A 5B 1Journal 52Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Linearly Convergent Frank-Wolfe-type Method for Smooth Convex Minimization over the Spectrahedron. CoRR Dan Garber
2025	J	`jnl`	Accelerated Frank-Wolfe Algorithms: Complementarity Conditions and Sparsity. CoRR Dan Garber
2025	A*	`conf`	Blackwell's Approachability with Approximation Algorithms. COLT Dan Garber, Mhna Massalha
2025	J	`jnl`	Blackwell's Approachability with Approximation Algorithms. CoRR Dan Garber, Mhna Massalha
2025	J	`jnl`	Eigenvalue problems via the multiplicative weights update method. Oper. Res. Lett. Dan Garber
2025	J	`jnl`	First-Order Sparse Convex Optimization: Better Rates with Sparse Updates. CoRR Dan Garber
2025	J	`jnl`	Low-rank extragradient methods for scalable semidefinite optimization. Oper. Res. Lett. Dan Garber, Atara Kaplan
2024	J	`jnl`	Low-Rank Extragradient Methods for Scalable Semidefinite Optimization. CoRR Dan Garber, Atara Kaplan
2024	A*	`conf`	Projection-Free Online Convex Optimization with Time-Varying Constraints. ICML Dan Garber, Ben Kretzu
2024	J	`jnl`	Projection-Free Online Convex Optimization with Time-Varying Constraints. CoRR Dan Garber, Ben Kretzu
2023	J	`jnl`	Efficiency of First-Order Methods for Low-Rank Tensor Recovery with the Tensor Nuclear Norm Under Strict Complementarity. CoRR Dan Garber, Atara Kaplan
2023	A	`conf`	Faster Projection-Free Augmented Lagrangian Methods via Weak Proximal Oracle. AISTATS Dan Garber, Tsur Livney, Shoham Sabach
2023	J	`jnl`	From Oja's Algorithm to the Multiplicative Weights Update Method with Applications. CoRR Dan Garber
2023	J	`jnl`	Linear convergence of Frank-Wolfe for rank-one matrix recovery without strong convexity. Math. Program. Dan Garber
2023	J	`jnl`	On the Efficient Implementation of the Matrix Exponentiated Gradient Algorithm for Low-Rank Matrix Optimization. Math. Oper. Res. Dan Garber, Atara Kaplan
2023	A*	`conf`	Projection-free Online Exp-concave Optimization. COLT Dan Garber, Ben Kretzu
2023	J	`jnl`	Projection-free Online Exp-concave Optimization. CoRR Dan Garber, Ben Kretzu
2022	J	`jnl`	Efficient Algorithms for High-Dimensional Convex Subspace Optimization via Strict Complementarity. CoRR Dan Garber, Ron Fisher
2022	J	`jnl`	Faster Projection-Free Augmented Lagrangian Methods via Weak Proximal Oracle. CoRR Dan Garber, Tsur Livney, Shoham Sabach
2022	A*	`conf`	Frank-Wolfe-based Algorithms for Approximating Tyler's M-estimator. NeurIPS Lior Danon, Dan Garber
2022	J	`jnl`	Frank-Wolfe-based Algorithms for Approximating Tyler's M-estimator. CoRR Lior Danon, Dan Garber
2022	A*	`conf`	Local Linear Convergence of Gradient Methods for Subspace Optimization via Strict Complementarity. NeurIPS Ron Fisher, Dan Garber
2022	J	`jnl`	Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems. CoRR Dan Garber, Atara Kaplan
2022	J	`jnl`	Low-Rank Mirror-Prox for Nonsmooth and Low-Rank Matrix Optimization Problems. CoRR Dan Garber, Atara Kaplan
2022	A*	`conf`	New Projection-free Algorithms for Online Convex Optimization with Adaptive Regret Guarantees. COLT Dan Garber, Ben Kretzu
2022	J	`jnl`	New Projection-free Algorithms for Online Convex Optimization with Adaptive Regret Guarantees. CoRR Dan Garber, Ben Kretzu
2021	J	`jnl`	Efficient Online Linear Optimization with Approximation Algorithms. Math. Oper. Res. Dan Garber
2021	A*	`conf`	Frank-Wolfe with a Nearest Extreme Point Oracle. COLT Dan Garber, Noam Wolf
2021	J	`jnl`	Frank-Wolfe with a Nearest Extreme Point Oracle. CoRR Dan Garber, Noam Wolf
2021	J	`jnl`	Improved complexities of conditional gradient-type methods with applications to robust matrix recovery problems. Math. Program. Dan Garber, Atara Kaplan, Shoham Sabach
2021	J	`jnl`	Learning Optimal Forecast Aggregation in Partial Evidence Environments. Math. Oper. Res. Yakov Babichenko, Dan Garber
2021	A*	`conf`	Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems. NeurIPS Atara Kaplan, Dan Garber
2021	J	`jnl`	On the Convergence of Projected-Gradient Methods with Low-Rank Projections for Smooth Convex Minimization over Trace-Norm Balls and Related Problems. SIAM J. Optim. Dan Garber
2021	A	`conf`	Revisiting Projection-free Online Learning: the Strongly Convex Case. AISTATS Ben Kretzu, Dan Garber
2020	A	`conf`	Improved Regret Bounds for Projection-free Bandit Convex Optimization. AISTATS Dan Garber, Ben Kretzu
2020	A*	`conf`	On the Convergence of Stochastic Gradient Descent with Low-Rank Projections for Convex Low-Rank Matrix Problems. COLT Dan Garber
2020	J	`jnl`	On the Convergence of Stochastic Gradient Descent with Low-Rank Projections for Convex Low-Rank Matrix Problems. CoRR Dan Garber
2020	J	`jnl`	On the Efficient Implementation of the Matrix Exponentiated Gradient Algorithm for Low-Rank Matrix Optimization. CoRR Dan Garber, Atara Kaplan
2020	A*	`conf`	Online Convex Optimization in the Random Order Model. ICML Dan Garber, Gal Korcia, Kfir Y. Levy
2020	A*	`conf`	Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and Sparsity. NeurIPS Dan Garber
2020	J	`jnl`	Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and Sparsity. CoRR Dan Garber
2020	J	`jnl`	Revisiting Projection-free Online Learning: the Strongly Convex Case. CoRR Dan Garber, Ben Kretzu
2019	A	`conf`	Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems. AISTATS Dan Garber, Atara Kaplan
2019	J	`jnl`	Improved Regret Bounds for Projection-free Bandit Convex Optimization. CoRR Dan Garber, Ben Kretzu
2019	J	`jnl`	Linear Convergence of Frank-Wolfe for Rank-One Matrix Recovery Without Strong Convexity. CoRR Dan Garber
2019	A	`conf`	Logarithmic Regret for Online Gradient Descent Beyond Strong Convexity. AISTATS Dan Garber
2019	J	`jnl`	On the Convergence of Projected-Gradient Methods with Low-Rank Projections for Smooth Convex Minimization over Trace-Norm Balls and Related Problems. CoRR Dan Garber
2019	A*	`conf`	On the Regret Minimization of Nonconvex Online Gradient Ascent for Online PCA. COLT Dan Garber
2019	J	`jnl`	Stochastic Canonical Correlation Analysis. J. Mach. Learn. Res. Chao Gao, Dan Garber, Nathan Srebro, Jialei Wang, Weiran Wang
2018	B	`conf`	Efficient coordinate-wise leading eigenvector computation. ALT Jialei Wang, Weiran Wang, Dan Garber, Nathan Srebro
2018	J	`jnl`	Fast Generalized Conditional Gradient Method with Applications to Matrix Recovery Problems. CoRR Dan Garber, Shoham Sabach, Atara Kaplan
2018	J	`jnl`	Fast Rates for Online Gradient Descent Without Strong Convexity via Hoffman's Bound. CoRR Dan Garber
2018	J	`jnl`	Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems. CoRR Dan Garber, Atara Kaplan
2018	J	`jnl`	Learning of Optimal Forecast Aggregation in Partial Evidence Environments. CoRR Yakov Babichenko, Dan Garber
2018	J	`jnl`	On the Regret Minimization of Nonconvex Online Gradient Ascent for Online PCA. CoRR Dan Garber
2017	A*	`conf`	Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis. ICML Dan Garber, Ohad Shamir, Nathan Srebro
2017	J	`jnl`	Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis. CoRR Dan Garber, Ohad Shamir, Nathan Srebro
2017	—	`conf`	Efficient Online Linear Optimization with Approximation Algorithms. NIPS Dan Garber
2017	J	`jnl`	Efficient Online Linear Optimization with Approximation Algorithms. CoRR Dan Garber
2017	J	`jnl`	Efficient coordinate-wise leading eigenvector computation. CoRR Jialei Wang, Weiran Wang, Dan Garber, Nathan Srebro
2017	J	`jnl`	Stochastic Canonical Correlation Analysis. CoRR Chao Gao, Dan Garber, Nathan Srebro, Jialei Wang, Weiran Wang
2016	J	`jnl`	A Linearly Convergent Variant of the Conditional Gradient Algorithm under Strong Convexity, with Applications to Online and Stochastic Optimization. SIAM J. Optim. Dan Garber, Elad Hazan
2016	—	`conf`	Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis. NIPS Weiran Wang, Jialei Wang, Dan Garber, Nati Srebro
2016	A*	`conf`	Faster Eigenvector Computation via Shift-and-Invert Preconditioning. ICML Dan Garber, Elad Hazan, Chi Jin, Sham M. Kakade, Cameron Musco, Praneeth Netrapalli, Aaron Sidford
2016	J	`jnl`	Faster Eigenvector Computation via Shift-and-Invert Preconditioning. CoRR Dan Garber, Elad Hazan, Chi Jin, Sham M. Kakade, Cameron Musco, Praneeth Netrapalli, Aaron Sidford
2016	—	`conf`	Faster Projection-free Convex Optimization over the Spectrahedron. NIPS Dan Garber
2016	J	`jnl`	Faster Projection-free Convex Optimization over the Spectrahedron. CoRR Dan Garber
2016	—	`conf`	Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes. NIPS Dan Garber, Ofer Meshi
2016	J	`jnl`	Linear-memory and Decomposition-invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes. CoRR Dan Garber, Ofer Meshi
2016	J	`jnl`	Sublinear time algorithms for approximate semidefinite programming. Math. Program. Dan Garber, Elad Hazan
2015	J	`jnl`	Fast and Simple PCA via Convex Optimization. CoRR Dan Garber, Elad Hazan
2015	A*	`conf`	Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets. ICML Dan Garber, Elad Hazan
2015	A*	`conf`	Online Learning of Eigenvectors. ICML Dan Garber, Elad Hazan, Tengyu Ma
2015	A*	`conf`	Online Principal Components Analysis. SODA Christos Boutsidis, Dan Garber, Zohar Shay Karnin, Edo Liberty
2014	J	`jnl`	Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets. CoRR Dan Garber, Elad Hazan
2013	J	`jnl`	A Polynomial Time Conditional Gradient Algorithm with Applications to Online and Stochastic Optimization CoRR Dan Garber, Elad Hazan
2013	J	`jnl`	Adaptive Universal Linear Filtering. IEEE Trans. Signal Process. Dan Garber, Elad Hazan
2013	A*	`conf`	Playing Non-linear Games with Linear Oracles. FOCS Dan Garber, Elad Hazan
2012	J	`jnl`	Almost Optimal Sublinear Time Algorithm for Semidefinite Programming CoRR Dan Garber, Elad Hazan
2011	—	`conf`	Approximating Semidefinite Programs in Sublinear Time. NIPS Dan Garber, Elad Hazan
2011	J	`jnl`	Universal MMSE Filtering With Logarithmic Adaptive Regret CoRR Dan Garber, Elad Hazan