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ORCIDYining Wang 0001
- > Home > Persons > Yining Wang 0001
Publications
- 2021
[j11]Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang
:
Near-optimal discrete optimization for experimental design: a regret minimization approach. Math. Program. 186(1): 439-478 (2021)- [c23]Yusha Liu, Yining Wang, Aarti Singh:
Smooth Bandit Optimization: Generalization to Holder Space. AISTATS 2021: 2206-2214 - 2020
- [i29]Yusha Liu, Yining Wang, Aarti Singh:
Smooth Bandit Optimization: Generalization to Hölder Space. CoRR abs/2012.06076 (2020) - 2019
- [j7]Yining Wang, Jialei Wang, Sivaraman Balakrishnan, Aarti Singh:
Rate optimal estimation and confidence intervals for high-dimensional regression with missing covariates. J. Multivar. Anal. 174 (2019) - [j6]Yining Wang, Yu-Xiang Wang, Aarti Singh:
A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data. IEEE Trans. Inf. Theory 65(2): 685-706 (2019) - [j5]Yining Wang, Sivaraman Balakrishnan, Aarti Singh:
Optimization of Smooth Functions With Noisy Observations: Local Minimax Rates. IEEE Trans. Inf. Theory 65(11): 7350-7366 (2019) - 2018
- [c19]Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh:
Stochastic Zeroth-order Optimization in High Dimensions. AISTATS 2018: 1356-1365 - [c18]Yining Wang, Aarti Singh:
Linear Quantization by Effective-Resistance Sampling. ICASSP 2018: 6927-6930 - [c17]Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh:
How Many Samples are Needed to Estimate a Convolutional Neural Network? NeurIPS 2018: 371-381 - [c15]Yining Wang, Sivaraman Balakrishnan, Aarti Singh:
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates. NeurIPS 2018: 4343-4354 - [i22]Yining Wang, Sivaraman Balakrishnan, Aarti Singh:
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates. CoRR abs/1803.08586 (2018) - [i20]Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh:
How Many Samples are Needed to Learn a Convolutional Neural Network? CoRR abs/1805.07883 (2018) - [i19]Simon S. Du, Yining Wang, Sivaraman Balakrishnan, Pradeep Ravikumar, Aarti Singh:
Robust Nonparametric Regression under Huber's ε-contamination Model. CoRR abs/1805.10406 (2018) - [i17]Yining Wang, Erva Ulu, Aarti Singh, Levent Burak Kara:
Efficient Load Sampling for Worst-Case Structural Analysis Under Force Location Uncertainty. CoRR abs/1810.10977 (2018) - 2017
- [j2]Yining Wang, Adams Wei Yu, Aarti Singh:
On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models. J. Mach. Learn. Res. 18: 143:1-143:41 (2017) - [j1]Yining Wang, Aarti Singh:
Provably Correct Algorithms for Matrix Column Subset Selection with Selectively Sampled Data. J. Mach. Learn. Res. 18: 156:1-156:42 (2017) - [c14]Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang:
Near-Optimal Design of Experiments via Regret Minimization. ICML 2017: 126-135 - [c13]Simon S. Du, Yining Wang, Aarti Singh:
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems. NIPS 2017: 445-455 - [i15]Yining Wang, Jialei Wang, Sivaraman Balakrishnan, Aarti Singh:
Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing Covariates. CoRR abs/1702.02686 (2017) - [i14]Simon S. Du, Yining Wang, Aarti Singh:
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems. CoRR abs/1702.06861 (2017) - [i11]Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh:
Stochastic Zeroth-order Optimization in High Dimensions. CoRR abs/1710.10551 (2017) - [i10]Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang:
Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approach. CoRR abs/1711.05174 (2017) - 2016
- [c12]Yining Wang, Aarti Singh:
Noise-Adaptive Margin-Based Active Learning and Lower Bounds under Tsybakov Noise Condition. AAAI 2016: 2180-2186 - [c11]Yining Wang, Yu-Xiang Wang, Aarti Singh:
Graph Connectivity in Noisy Sparse Subspace Clustering. AISTATS 2016: 538-546 - [c9]Bo Li, Yining Wang, Aarti Singh, Yevgeniy Vorobeychik:
Data Poisoning Attacks on Factorization-Based Collaborative Filtering. NIPS 2016: 1885-1893 - [i9]Yining Wang, Aarti Singh:
Minimax Subsampling for Estimation and Prediction in Low-Dimensional Linear Regression. CoRR abs/1601.02068 (2016) - [i6]Bo Li, Yining Wang, Aarti Singh, Yevgeniy Vorobeychik:
Data Poisoning Attacks on Factorization-Based Collaborative Filtering. CoRR abs/1608.08182 (2016) - [i5]Yining Wang, Yu-Xiang Wang, Aarti Singh:
A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data. CoRR abs/1610.07650 (2016) - 2015
- [c8]Yining Wang, Aarti Singh:
Column Subset Selection with Missing Data via Active Sampling. AISTATS 2015 - [c7]Yining Wang, Aarti Singh:
An empirical comparison of sampling techniques for matrix column subset selection. Allerton 2015: 1069-1074 - [c5]Yining Wang, Yu-Xiang Wang, Aarti Singh:
A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data. ICML 2015: 1422-1431 - [c4]Yining Wang, Yu-Xiang Wang, Aarti Singh:
Differentially private subspace clustering. NIPS 2015: 1000-1008 - [i4]Yining Wang, Yu-Xiang Wang, Aarti Singh:
Clustering Consistent Sparse Subspace Clustering. CoRR abs/1504.01046 (2015) - [i3]Yining Wang, Aarti Singh:
Provably Correct Active Sampling Algorithms for Matrix Column Subset Selection with Missing Data. CoRR abs/1505.04343 (2015) - 2014
- [i2]Yining Wang, Aarti Singh:
Noise-adaptive Margin-based Active Learning for Multi-dimensional Data. CoRR abs/1406.5383 (2014)
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