If the facts don't fit the theory, change the facts - Einstein.
I'm a PhD student in the Computer Science Department at Princeton University, advised by Sanjeev Arora. Previously I obtained my B.S.E. degree at Tsinghua University.
I am working on Theoretical Machine Learning, in particular, designing efficient, provable algorithms for practical machine learning problems. I am also very interested in convex/non-convex geometry.
$l at princeton.edu, replace $ with my first name.
Linear algebraic structure of word senses, with applications to polysemy. With Sanjeev Arora Yingyu Liang, Tengyu Ma and Andrej Risteski. Manuscript
Faster Principal Component Regression via Optimal Polynomial Approximation to sgn(x). With Zeyuan Allen-Zhu. Submitted
Fast Global Convergence of Online PCA. With Zeyuan Allen-Zhu. Submitted
Doubly Accelerated Methods for Faster CCA and Generalized Eigendecomposition. With Zeyuan Allen-Zhu. Submitted
RAND-WALK: a latent variable model approach to word embeddings. With Sanjeev Arora, Yingyu Liang, Tengyu Ma and Andrej Risteski. Accepted to Transactions of the Association for Computational Linguistics (TACL)
Even Faster SVD Decomposition Yet Without Agonizing Pain. With Zeyuan Allen-Zhu. NIPS 2016
Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods. With Andrej Risteski. NIPS 2016
Tight algorithms and lower bounds for approximately convex optimization. With Andrej Risteski. NIPS 2016
Non-negative matrix factorization using a decode-and-update approach. With Yingyu Liang and Andrej Risteski. NIPS 2016
Recovery guarantee of weighted low-rank approximation via alternating minimization. With Yingyu Liang and Andrej Risteski. ICML 2016
A Theoretical Analysis of NDCG Ranking Measures. With Yining Wang, Liwei Wang, Di He, Wei Chen and Tie-Yan Liu. COLT 2013
COS423: Theory of Algorithms, Fall 2016. TA
COS521: Advance algorithm design, Spring 2016. TA