I am a third year PhD student in the Machine Learning Department at Carnegie Mellon University. My advisor is Aarti Singh. Before coming to CMU, I was an undergraduate student at the Yao Class in Tsinghua University.
I am generally interested in statistical machine learning. Some topics that interest me include matrix completion and approximation, column subset selection and subspace clustering. I also want to know whether these tasks can be solved when only partial observations are available, and how can we improve over existing approaches by adaptively sampling/sensing in a feedback-driven manner.
Previously I have worked on Bayesian nonparametric modeling and the method of moments (spectral methods). I'm still interested in these topics. If you have common interests, feel free to stop by my office and we can have a chat.Download CV
PhD student in Machine Learning, School of Computer Science
Advisor: Aarti Singh
2014 - present
B. Eng. in Computer Science
Undergraduate thesis: Spectral Methods in Supervised Topic Modeling
Thesis advisor: Jun Zhu
2010 - 2014
Supervisor: Dengyong (Denny) Zhou and Chong Wang.
Supervisor: Petros Efstathopoulos and Kevin Roundy.
RA at State Key Laboratory of Intelligent Technology and Systems.
Advisor: Jun Zhu
Undergraduate exchange program at Department of EECS
Recent papers Full publication list
Simon Du, Yining Wang and Aarti Singh. On the Power of Truncated SVD for General High-rank Matrix Estimation Problems.
Yining Wang, Jialei Wang, Sivaraman Balakrishnan and Aarti Singh. Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing Covariates.
Yining Wang, Yu-Xiang Wang and Aarti Singh. A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data. Short version appeared in ICML 2015.
Bo Li**, Yining Wang**, Aarti Singh and Yevgeniy Vorobeychik. Data Poisoning Attacks on Factorization-Based Collaborative Filtering. To appear in NIPS 2016.
Yining Wang, Anima Anandkumar. Online and Differentially Private Tensor Decomposition. To appear in NIPS 2016.
Yining Wang, Adams Wei Yu and Aarti Singh. On Computationally Tractable Selection of Experiments in Regression Models.
Maria-Florina Balcan*, Simon Du*, Yining Wang*, Adams Wei Yu*. An Improved Gap-Dependency Analysis of the Noisy Power Method. In COLT 2016.
Yining Wang, Yu-Xiang Wang and Aarti Singh. Graph Connectivity in Noisy Sparse Subspace Clustering. In AISTATS 2016.