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

Sampling Engineering & Materials Science
Recovery Engineering & Materials Science
Channel capacity Engineering & Materials Science
Phase Retrieval Mathematics
Compressed sensing Engineering & Materials Science
Random Systems Mathematics
Quadratic Systems Mathematics
Convex optimization Engineering & Materials Science

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Research Output 2010 2019

  • 662 Citations
  • 11 h-Index
  • 20 Conference contribution
  • 18 Article
  • 1 Paper
  • 1 Conference article
2 Citations (Scopus)

Gradient descent with random initialization: fast global convergence for nonconvex phase retrieval

Chen, Y., Chi, Y., Fan, J. & Ma, C., Jul 1 2019, In : Mathematical Programming. 176, 1-2, p. 5-37 33 p.

Princeton University

Research output: Contribution to journalArticle

Phase Retrieval
Gradient Descent
Global Convergence
Learning systems
1 Citation (Scopus)
Matrix Completion
Blind Deconvolution
Phase Retrieval
Statistical Estimation
Gradient Descent
2 Citations (Scopus)

Spectral method and regularized mle are both optimal for top-K ranking

Chen, Y., Fan, J., Ma, C. & Wang, K., Jan 1 2019, In : Annals of Statistics. 47, 4, p. 2204-2235 32 p.

Princeton University

Research output: Contribution to journalArticle

Spectral Methods
Pairwise Comparisons
Maximum Likelihood Estimator
1 Citation (Scopus)

The likelihood ratio test in high-dimensional logistic regression is asymptotically a rescaled Chi-square

Sur, P., Chen, Y. & Candès, E. J., Oct 1 2019, In : Probability Theory and Related Fields. 175, 1-2, p. 487-558 72 p.

Princeton University

Research output: Contribution to journalArticle

Likelihood Ratio Test
Logistic Regression
Log-likelihood Ratio
Wilks' Theorem

Implicit regularization in nonconvex statistical estimation: Gradient descent converges linearly for phase retrieval and matrix completion

Ma, C., Wang, K., Chi, Y. & Chen, Y., Jan 1 2018, 35th International Conference on Machine Learning, ICML 2018. Dy, J. & Krause, A. (eds.). International Machine Learning Society (IMLS), p. 5264-5331 68 p. (35th International Conference on Machine Learning, ICML 2018; vol. 8).

Princeton University

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