If you made any changes in Pure, your changes will be visible here soon.

Fingerprint Dive into the research topics where Elad Hazan is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 3 Similar Profiles
Convex optimization Engineering & Materials Science
Regret Mathematics
Learning systems Engineering & Materials Science
Online Learning Mathematics
Stochastic Optimization Mathematics
Learning algorithms Engineering & Materials Science
Online Optimization Mathematics
Convex Optimization Mathematics

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2015 2018

Research Output 2003 2018

Hyperparameter optimization: A spectral approach

Hazan, E. E., Klivans, A. & Yuan, Y., Jan 1 2018.

Princeton University

Research output: Contribution to conferencePaper

Decision trees
neural network
Polynomials
Compressed sensing
Boolean functions

Online improper learning with an approximation oracle

Hazan, E. E., Hu, W., Li, Y. & Li, Z., Jan 1 2018, In : Advances in Neural Information Processing Systems. 2018-December, p. 5652-5660 9 p.

Princeton University

Research output: Contribution to journalConference article

Approximation algorithms

Online learning of quantum states

Aaronson, S., Hazan, E. E., Chen, X., Kale, S. & Nayak, A., Jan 1 2018, In : Advances in Neural Information Processing Systems. 2018-December, p. 8962-8972 11 p.

Princeton University

Research output: Contribution to journalConference article

Convex optimization
Oils and fats

On the optimization of deep networks: Implicit acceleration by overparameterization

Arora, S., Cohen, N. & Hazan, E. E., Jan 1 2018, 35th International Conference on Machine Learning, ICML 2018. Krause, A. & Dy, J. (eds.). International Machine Learning Society (IMLS), p. 372-389 18 p. (35th International Conference on Machine Learning, ICML 2018; vol. 1).

Princeton University

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Linear regression
Neural networks
Experiments
Deep learning

Spectral filtering for general linear dynamical systems

Hazan, E. E., Lee, H., Singh, K., Zhang, C. & Zhang, Y., Jan 1 2018, In : Advances in Neural Information Processing Systems. 2018-December, p. 4634-4643 10 p.

Princeton University

Research output: Contribution to journalConference article

dynamical systems
system identification
learning
polynomials
radii