Research output per year
Research output per year
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Dive into the research topics where Dan Garber is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Faster Projection-Free Augmented Lagrangian Methods via Weak Proximal Oracle
Garber, D., Livney, T. & Sabach, S., 2023, In: Proceedings of Machine Learning Research. 206, p. 7213-7238 26 p.Research output: Contribution to journal › Conference article › peer-review
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On the Efficient Implementation of the Matrix Exponentiated Gradient Algorithm for Low-Rank Matrix Optimization
Garber, D. & Kaplan, A., 2023, In: Mathematics of Operations Research. 48, 4, p. 2094-2128 35 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Projection-free Online Exp-concave Optimization
Garber, D. & Kretzu, B., 2023, In: Proceedings of Machine Learning Research. 195, p. 1259-1284 26 p.Research output: Contribution to journal › Conference article › peer-review
1 Scopus citations -
Frank-Wolfe-based Algorithms for Approximating Tyler* M-estimator
Danon, L. & Garber, D., 2022, Advances in Neural Information Processing Systems 35 - 36th Conference on Neural Information Processing Systems, NeurIPS 2022. Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A. (eds.). (Advances in Neural Information Processing Systems; vol. 35).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
2 Scopus citations -
Local Linear Convergence of Gradient Methods for Subspace Optimization via Strict Complementarity
Fisher, R. & Garber, D., 2022, Advances in Neural Information Processing Systems 35 - 36th Conference on Neural Information Processing Systems, NeurIPS 2022. Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A. (eds.). (Advances in Neural Information Processing Systems; vol. 35).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review