Dan Garber
Orcid: 0000-0002-5181-9193
According to our database1,
Dan Garber
authored at least 48 papers
between 2011 and 2024.
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Bibliography
2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
Linear convergence of Frank-Wolfe for rank-one matrix recovery without strong convexity.
Math. Program., May, 2023
CoRR, 2023
Efficiency of First-Order Methods for Low-Rank Tensor Recovery with the Tensor Nuclear Norm Under Strict Complementarity.
CoRR, 2023
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
CoRR, 2022
Efficient Algorithms for High-Dimensional Convex Subspace Optimization via Strict Complementarity.
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Local Linear Convergence of Gradient Methods for Subspace Optimization via Strict Complementarity.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
New Projection-free Algorithms for Online Convex Optimization with Adaptive Regret Guarantees.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
2021
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., 2021
Improved complexities of conditional gradient-type methods with applications to robust matrix recovery problems.
Math. Program., 2021
Math. Oper. Res., 2021
Math. Oper. Res., 2021
Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Conference on Learning Theory, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
On the Efficient Implementation of the Matrix Exponentiated Gradient Algorithm for Low-Rank Matrix Optimization.
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
On the Convergence of Stochastic Gradient Descent with Low-Rank Projections for Convex Low-Rank Matrix Problems.
Proceedings of the Conference on Learning Theory, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
Proceedings of the Conference on Learning Theory, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
2018
Fast Generalized Conditional Gradient Method with Applications to Matrix Recovery Problems.
CoRR, 2018
CoRR, 2018
Proceedings of the Algorithmic Learning Theory, 2018
2017
Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis.
Proceedings of the 34th International Conference on Machine Learning, 2017
2016
A Linearly Convergent Variant of the Conditional Gradient Algorithm under Strong Convexity, with Applications to Online and Stochastic Optimization.
SIAM J. Optim., 2016
Math. Program., 2016
Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
2015
Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015
Proceedings of the 32nd International Conference on Machine Learning, 2015
Proceedings of the 32nd International Conference on Machine Learning, 2015
2013
A Polynomial Time Conditional Gradient Algorithm with Applications to Online and Stochastic Optimization
CoRR, 2013
Proceedings of the 54th Annual IEEE Symposium on Foundations of Computer Science, 2013
2012
2011
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011