Yen-Huan Li

picture

Research interests:

  • High-dimensional statistics
  • Machine learning
  • Convex optimization
  • Classical and quantum information theories

Contact Address 

EPFL-STI-IEL-LIONS

ELD 243 (Batiment EL)

Station 11

1015 Lausanne, Switzerland

 +41(0) 21 693 26 05

people@EPFL page

email: yen-huan.li@epfl.ch

Biography 

I received a B.S.E. degree in Electrical Engineering with a minor in Economics in 2008, and an M.S. degree in Communication Engineering in 2010, both from National Taiwan University. I served in the R.O.C. Army as a signal platoon leader from 2010 to 2011. I was a research assistant at the Research Center for Information Technology Innovation, Academia Sinica, from 2011 to 2012. Since 2012, I have been a doctoral assistant at EPFL, advised by Prof. Volkan Cevher. My research topics revolve around high-dimensional statistical data analysis.
 
Links
 

 

 

PUBLICATIONS

Y.-H. Li; V. Cevher : Convergence of the Exponentiated Gradient Method with Armijo Line Search; Journal of Optimization Theory and Applications. 2018-12-03. DOI : 10.1007/s10957-018-1428-9.
Y.-H. Li / V. Cevher (Dir.) : Learning without Smoothness and Strong Convexity. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8765.
B. Gözcü; R. Karimi Mahabadi; Y.-H. Li; E. Ilıcak; T. Çukur et al. : Learning-Based Compressive MRI; IEEE Transactions On Medical Imaging. 2018. DOI : 10.1109/TMI.2018.2832540.
V. Cevher; Y.-h. Li; I. Bogunovic; L. Baldassarre; J. Scarlett et al. ; Learning-based subsampling. US2017109650 . 2017.
N. Zerbib; Y.-H. Li; Y.-P. Hsieh; V. Cevher : Estimation Error of the Constrained Lasso. 2016. 54th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, September 27-30, 2016.
Y.-H. Li; V. Cevher : Learning Data Triage: Linear Decoding Works for Compressive MRI. 2016. 41st IEEE International Conference on Acoustics, Speech and Signal Processing. p. 4034-4038.
G. Odor; Y.-H. Li; A. Yurtsever; Y.-P. Hsieh; Q. Tran Dinh et al. : Frank-Wolfe Works for Non-Lipschitz Continuous Gradient Objectives: Scalable Poisson Phase Retrieval. 2016. 41st IEEE International Conference on Acoustics, Speech and Signal Processing. p. 6230-6234.
L. Baldassarre; Y.-H. Li; J. Scarlett; B. Gözcü; I. Bogunovic et al. : Learning-Based Compressive Subsampling; IEEE Journal on Selected Topics in Signal Processing. 2016. DOI : 10.1109/Jstsp.2016.2548442.
Q. Tran Dinh; Y.-H. Li; V. Cevher : Composite convex minimization involving self-concordant-like cost functions. 2015. Modelling, Computation and Optimization in Information Systems and Management Sciences (MCO 2015), Metz, France, May 11-13, 2015.
Q. Tran Dinh; Y.-H. Li; V. Cevher : Composite convex minimization involving self-concordant-like cost functions; Tech. Report. 2015.
Y.-H. Li; Y.-P. Hsieh; N. Zerbib; V. Cevher : A Geometric View on Constrained M-Estimators. 2015.
Y.-H. Li; V. Cevher : Consistency of $\ell_1$-Regularized Maximum-Likelihood for Compressive Poisson Regression. 2015. 40th IEEE Int. Conf. Acoustics, Speech and Signal Processing, Brisbane, Australia, April 19-24, 2015.
Y.-H. Li; J. Scarlett; P. Ravikumar; V. Cevher : Sparsistency of $\ell_1$-Regularized $M$-Estimators. 2015. The 18th International Conference on Artificial Intelligence and Statistics, San Diego, California, USA, May 9-12, 2015.
Q. Tran Dinh; Y.-H. Li; V. Cevher : Barrier Smoothing for Nonsmooth Convex Minimization. 2014. IEEE International Conference on Acoustics, Speech, and Signal Processing, Florence, Italy, May 4-9, 2014.