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 work on Machine Learning. My goal is to designing efficient and 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.
Algorithmic Regularization in Over-parameterized Matrix Recovery. With Tengyu Ma and Hongyang Zhang. Submitted
Neon2: Finding Local Minima via First-Order Oracles. With Zeyuan Allen-Zhu. Submitted
Operator Scaling via Geodesically Convex Optimization, Invariant Theory and Polynomial Identity Testing. With Zeyuan Allen-Zhu, Ankit Garg, Rafael Oliveira and Avi Wigderson. STOC 2018
An homotopy method for Lp regression provably beyond self-concordance and in input-sparsity time. With Sebastien Bubeck, Michael B. Cohen and Yin Tat Lee. STOC 2018
Linear algebraic structure of word senses, with applications to polysemy. With Sanjeev Arora, Yingyu Liang, Tengyu Ma and Andrej Risteski. TACL 2018
Sparsity, variance and curvature in multi-armed bandits. With Sebastien Bubeck and Michael B. Cohen. ALT 2018
An Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model. With Xi Chen and Jieming Mao. SODA 2018
Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls. With Zeyuan Allen-Zhu, Elad Hazan and Wei Hu. NIPS 2017
Convergence Analysis of Two-layer Neural Networks with ReLU Activation . With Yang Yuan. NIPS 2017
Much Faster Algorithms for Matrix Scaling. With Zeyuan Allen-Zhu, Rafael Oliveira and Avi Wigderson. FOCS 2017
Fast Global Convergence of Online PCA. With Zeyuan Allen-Zhu. FOCS 2017
Near-Optimal Design of Experiments via Regret Minimization. With Zeyuan Allen-Zhu, Aarti Singh and Yining Wang. ICML 2017
Provable Alternating Gradient Descent for Non-negative Matrix Factorization with Strong Correlations. With Yingyu Liang. ICML 2017
Follow the Compressed Leader: Faster Algorithm for Matrix Multiplicative Weight Updates. With Zeyuan Allen-Zhu. ICML 2017
Faster Principal Component Regression via Optimal Polynomial Approximation to sgn(x). With Zeyuan Allen-Zhu. ICML 2017
Doubly Accelerated Methods for Faster CCA and Generalized Eigendecomposition. With Zeyuan Allen-Zhu. ICML 2017
RAND-WALK: a latent variable model approach to word embeddings. With Sanjeev Arora, Yingyu Liang, Tengyu Ma and Andrej Risteski. TACL 2016
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
Recovery Guarantee of Non-negative Matrix Factorization via Alternating Updates. 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