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Projects

Research Output

Stochastic Subgradient Method Converges on Tame Functions

Davis, D., Drusvyatskiy, D., Kakade, S. & Lee, J. D., Feb 1 2020, In : Foundations of Computational Mathematics. 20, 1, p. 119-154 36 p.

Princeton University

Research output: Contribution to journalArticle

Communication-Efficient Distributed Statistical Inference

Jordan, M. I., Lee, J. D. & Yang, Y., Apr 3 2019, In : Journal of the American Statistical Association. 114, 526, p. 668-681 14 p.

Research output: Contribution to journalArticle

First-order methods almost always avoid strict saddle points

Lee, J. D., Panageas, I., Piliouras, G., Simchowitz, M., Jordan, M. I. & Recht, B., Jul 1 2019, In : Mathematical Programming. 176, 1-2, p. 311-337 27 p.

Research output: Contribution to journalArticle

Theoretical insights into the optimization landscape of over-parameterized shallow neural networks

Soltanolkotabi, M., Javanmard, A. & Lee, J. D., Feb 2019, In : IEEE Transactions on Information Theory. 65, 2, p. 742-769 28 p., 8409482.

Research output: Contribution to journalArticle

Adding one neuron can eliminate all bad local minima

Liang, S., Sun, R., Lee, J. D. & Srikant, R., Jan 1 2018, In : Advances in Neural Information Processing Systems. 2018-December, p. 4350-4360 11 p.

Princeton University

Research output: Contribution to journalConference article