(*alphabetic author order, **equal contribution)
The headings refer to the completion dates; the publication dates are given at the end of the citations.
2018
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates.
By Yining Wang, Sivaraman Balakrishnan and Aarti Singh.
[slides]
Near-Linear Time Local Polynomial Nonparametric Estimation.
By Yining Wang, Yi Wu and Simon Du.
2017
Convergence Rates of Latent Topic Models Under Relaxed Identifiability Conditions.
By Yining Wang.
Stochastic Zeroth-order Optimization in High Dimensions.
By Yining Wang, Simon Du, Sivaraman Balakrishnan and Aarti Singh.
[slides]
In AISTATS 2018 (oral), Playa Blanca, Spain.
A Note on Tight Lower Bound for MNL-Bandit Assortment Selection Models.
By Xi Chen* and Yining Wang*.
Non-stationary Stochastic Optimization with Local Spatial and Temporal Changes.
By Xi Chen*, Yining Wang* and Yu-Xiang Wang*. [slides]
Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approach.
By Zeyuan Allen-Zhu*, Yuanzhi Li*, Aarti Singh* and Yining Wang*.
[code]
[slides]
Preliminary version in ICML 2017, Sydney, Australia.
A two-page astract presented at the DSML Workshop in NIPS 2017, Long Beach, USA.
Sequence Modeling via Segmentations.
By Chong Wang, Yining Wang, Po-Sen Huang, Abdelrahman Mohamed, Dengyong Zhou and Li Deng.
In ICML 2017, Sydney, Australia.
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems.
By Simon Du, Yining Wang and Aarti Singh.
In NIPS 2017, Long Beach, USA.
Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing Covariates.
By Yining Wang, Jialei Wang, Sivaraman Balakrishnan and Aarti Singh.
2016
Data Poisoning Attacks on Factorization-Based Collaborative Filtering.
By Bo Li**, Yining Wang**, Aarti Singh and Yevgeniy Vorobeychik.
In NIPS 2016, Barcelona, Spain.
Online and Differentially Private Tensor Decomposition.
By Yining Wang and Anima Anandkumar.
In NIPS 2016, Barcelona, Spain.
An Improved Gap-Dependency Analysis of the Noisy Power Method.
By Maria-Florina Balcan*, Simon Du*, Yining Wang* and Adams Wei Yu*.
In COLT 2016, New York, USA.
On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models.
By Yining Wang, Adams Wei Yu and Aarti Singh.
[code]
[slides]
[journal link]
Journal of Machine Learning Research, 18(143):1-41, 2017.
A short abstract appeared at the DEML Workshop in ICML 2016, New York, USA.
An extension to linear quantization appeared in ICASSP 2018, Calgary, Canada.
[slides]
2015
Fast and Guaranteed Tensor Decomposition via Sketching.
By Yining Wang, Hsiao-Yu Fish Tung, Alex Smola and Anima Anandkumar.
[code]
In NIPS 2015 (spotlight), Montreal, Canada.
The theoretical analysis in this paper is sub-optimal. Please refer to our new paper
for a cleaner and improved analysis of orthogonal tensor decomposition via noisy power method.
Differentially Private Subspace Clustering.
By Yining Wang, Yu-Xiang Wang and Aarti Singh.
In NIPS 2015, Montreal, Canada.
Graph Connectivity in Noisy Sparse Subspace Clustering.
By Yining Wang, Yu-Xiang Wang and Aarti Singh.
In AISTATS 2016, Cadiz, Spain.
A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data.
By Yining Wang, Yu-Xiang Wang and Aarti Singh.
Preliminary version
in ICML 2015, Lille, France.
DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics.
By Yining Wang and Jun Zhu. [code]
In ICML 2015, Lille, France.
Provably Correct Active Sampling Algorithms for Matrix Column Subset Selection with Missing Data.
By Yining Wang and Aarti Singh.
Journal of Machine Learning Research, to appear.
Preliminary version in AISTATS 2015, San Diego, USA.
A follow-up note with empirical comparisons in Allerton 2015, Monticello, USA. [slides]
2014
Noise-adaptive Margin-based Active Learning and Lower Bounds under Tsybakov Noise Condition.
By Yining Wang and Aarti Singh.
In AAAI 2016 (oral), Phoenix, USA. [slides]
Direct Learning to Rank And Rerank.
By Cynthia Rudin and Yining Wang.
In AISTATS 2018, Playa Blanca, Spain.
Spectral Learning for Supervised Topic Models.
By Yong Ren**, Yining Wang** and Jun Zhu.
[code]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(3):726-739, 2018.
Preliminary version in NIPS 2014, Montreal, Canada.
Small-variance Asymptotics for Dirichlet Process Mixtures of SVMs.
By Yining Wang and Jun Zhu.
[slides]
[code]
In AAAI 2014 (oral), Quebec City, Canada.
Harvesting Motion Patterns in Still Images from the Internet.
By Jiajun Wu, Yining Wang, Zhulin Li and Zhuowen Tu.
In CogSci 2014, Quebec City, Canada.
2013 and before
A Theoretical Analysis of NDCG Type Ranking Measures.
By Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Wei Chen and Tie-Yan Liu.
In COLT 2013, Princeton, USA.
Building Large Collections of Chinese and English Medical Terms from Semi-Structured and Encyclopedia Websites.
By Yan Xu, Yining Wang, Jian-Tao Sun, Jianwen Zhang, Junichi Tsujii and Eric Chang.
PLoS One, 8(7):e67526, 2013.
Joint segmentation and named entity recognition using dual decomposition in Chinese discharge summaries.
By Yan Xu, Yining Wang, Tianren Liu, Jiahua Liu, Yubo Fan, Yi Qian, Junichi Tsujii and Eric Chang.
Journal of the American Medical Informatics Association, 21:e84-e92, 2014.
An end-to-end system to identify temporal relation in discharge summaries: 2012 i2b2 challenge.
By Yan Xu, Yining Wang, Tianren Liu, Junichi Tsujii and Eric Chang.
Journal of the Americal Medical Informatics Association, 20:849-858, 2013.
FMTCP: A Fountain Code-Based Multipath Transmission Control Protocol.
By Yong Cui, Lian Wang, Xin Wang, Hongyi Wang and Yining Wang.
IEEE/ACM Transactions on Networking, 23(2):465-478, 2015.