Dan Garber
28 papers · 2011–2025 · 6 conferences · across top CS/AI conferences
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(28)
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Conferences
NIPS (9)
COLT (6)
ICML (6)
AISTATS (5)
ALT (1)
JMLR (1)
Top co-authors
Keywords
convex optimization
(9)
frank-wolfe algorithm
(5)
online learning
(5)
stochastic optimization
(4)
projection-free optimization
(4)
conditional gradient
(4)
matrix computation
(3)
regret bound
(3)
linear convergence
(3)
principal component analysis
(3)
online convex optimization
(3)
eigenvector computation
(3)
approximation algorithm
(2)
streaming algorithm
(2)
frank-wolfe method
(2)
singular value decomposition
(2)
canonical correlation analysis
(2)
low-rank matrix
(2)
regret minimization
(2)
matrix recovery
(2)
Papers
Blackwellβs Approachability with Approximation Algorithms
COLT 2025
Projection-Free Online Convex Optimization with Time-Varying Constraints
ICML 2024
Projection-free Online Exp-concave Optimization
COLT 2023
Faster Projection-Free Augmented Lagrangian Methods via Weak Proximal Oracle
AISTATS 2023
Local Linear Convergence of Gradient Methods for Subspace Optimization via Strict Complementarity
NIPS 2022
New Projection-free Algorithms for Online Convex Optimization with Adaptive Regret Guarantees
COLT 2022
Frank-Wolfe-based Algorithms for Approximating Tyler's M-estimator
NIPS 2022
Frank-Wolfe with a Nearest Extreme Point Oracle
COLT 2021
Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems
NIPS 2021
Revisiting Projection-free Online Learning: the Strongly Convex Case
AISTATS 2021
Online Convex Optimization in the Random Order Model
ICML 2020
Improved Regret Bounds for Projection-free Bandit Convex Optimization
AISTATS 2020
On the Convergence of Stochastic Gradient Descent with Low-Rank Projections for Convex Low-Rank Matrix Problems
COLT 2020
Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and Sparsity
NIPS 2020
Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems
AISTATS 2019
Stochastic Canonical Correlation Analysis
JMLR 2019
On the Regret Minimization of Nonconvex Online Gradient Ascent for Online PCA
COLT 2019
Logarithmic Regret for Online Gradient Descent Beyond Strong Convexity
AISTATS 2019
Efficient coordinate-wise leading eigenvector computation
ALT 2018
Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis
ICML 2017
Efficient Online Linear Optimization with Approximation Algorithms
NIPS 2017
Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis
NIPS 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning
ICML 2016
Faster Projection-free Convex Optimization over the Spectrahedron
NIPS 2016
Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes
NIPS 2016
Online Learning of Eigenvectors
ICML 2015
Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets
ICML 2015
Approximating Semidefinite Programs in Sublinear Time
NIPS 2011