A Theoretical Analysis of NDCG Type Ranking Measures. - Yining Wang 001; Liwei Wang 001; Yuanzhi Li; Di He 001; Tie-Yan Liu (COLT, 2013)

A Theoretical Analysis of NDCG Type Ranking Measures - Yining Wang 001; Liwei Wang 001; Yuanzhi Li; Di He 001; Tie-Yan Liu; Wei Chen 034 (CoRR, 2013)

Small-Variance Asymptotics for Dirichlet Process Mixtures of SVMs. - Yining Wang 001; Jun Zhu 001 (AAAI, 2014)

Spectral Methods for Supervised Topic Models. - Yining Wang 001; Jun Zhu 001 (NIPS, 2014)

Noise-adaptive Margin-based Active Learning for Multi-dimensional Data. - Yining Wang 001; Aarti Singh (CoRR, 2014)

Column Subset Selection with Missing Data via Active Sampling. - Yining Wang 001; Aarti Singh (AISTATS, 2015)

An empirical comparison of sampling techniques for matrix column subset selection. - Yining Wang 001; Aarti Singh (Allerton, 2015)

A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data. - Yining Wang 001; Yu-Xiang Wang 003; Aarti Singh (ICML, 2015)

DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics. - Yining Wang 001; Jun Zhu 001 (ICML, 2015)

Differentially private subspace clustering. - Yining Wang 001; Yu-Xiang Wang 003; Aarti Singh (NIPS, 2015)

Provably Correct Active Sampling Algorithms for Matrix Column Subset Selection with Missing Data. - Yining Wang 001; Aarti Singh (CoRR, 2015)

Clustering Consistent Sparse Subspace Clustering. - Yining Wang 001; Yu-Xiang Wang 003; Aarti Singh (CoRR, 2015)

Noise-Adaptive Margin-Based Active Learning and Lower Bounds under Tsybakov Noise Condition. - Yining Wang 001; Aarti Singh (AAAI, 2016)

Graph Connectivity in Noisy Sparse Subspace Clustering. - Yining Wang 001; Yu-Xiang Wang 003; Aarti Singh (AISTATS, 2016)

An Improved Gap-Dependency Analysis of the Noisy Power Method. - Maria-Florina Balcan; Simon Shaolei Du; Yining Wang 001; Adams Wei Yu (COLT, 2016)

Data Poisoning Attacks on Factorization-Based Collaborative Filtering. - Bo Li 026; Yining Wang 001; Aarti Singh; Yevgeniy Vorobeychik (NIPS, 2016)

Minimax Subsampling for Estimation and Prediction in Low-Dimensional Linear Regression. - Yining Wang 001; Aarti Singh (CoRR, 2016)

Near-Optimal Design of Experiments via Regret Minimization. - Zeyuan Allen-Zhu; Yuanzhi Li; Aarti Singh; Yining Wang 001 (ICML, 2017)

On the Power of Truncated SVD for General High-rank Matrix Estimation Problems. - Simon S. Du; Yining Wang 001; Aarti Singh (NIPS, 2017)

Non-stationary Stochastic Optimization with Local Spatial and Temporal Changes. - Xi Chen 010; Yining Wang 001; Yu-Xiang Wang 003 (CoRR, 2017)

A Note on Tight Lower Bound for MNL-Bandit Assortment Selection Models. - Xi Chen 010; Yining Wang 001 (CoRR, 2017)

Provably Correct Algorithms for Matrix Column Subset Selection with Selectively Sampled Data. - Yining Wang 001; Aarti Singh (J. Mach. Learn. Res., 2017)

On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models. - Yining Wang 001; Adams Wei Yu; Aarti Singh (J. Mach. Learn. Res., 2017)

Stochastic Zeroth-order Optimization in High Dimensions. - Yining Wang 001; Simon S. Du; Sivaraman Balakrishnan; Aarti Singh (AISTATS, 2018)

Linear Quantization by Effective-Resistance Sampling. - Yining Wang 001; Aarti Singh (ICASSP, 2018)

How Many Samples are Needed to Estimate a Convolutional Neural Network? - Simon S. Du; Yining Wang 001; Xiyu Zhai; Sivaraman Balakrishnan; Ruslan Salakhutdinov; Aarti Singh (NeurIPS, 2018)

Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models. - Yining Wang 001; Xi Chen 010; Yuan Zhou 007 (NeurIPS, 2018)

Near-Linear Time Local Polynomial Nonparametric Estimation. - Yining Wang 001; Yi Wu 013; Simon S. Du (CoRR, 2018)

How Many Samples are Needed to Learn a Convolutional Neural Network? - Simon S. Du; Yining Wang 001; Xiyu Zhai; Sivaraman Balakrishnan; Ruslan Salakhutdinov; Aarti Singh (CoRR, 2018)

Robust Nonparametric Regression under Huber's ε-contamination Model. - Simon S. Du; Yining Wang 001; Sivaraman Balakrishnan; Pradeep Ravikumar; Aarti Singh (CoRR, 2018)

Dynamic Assortment Selection under the Nested Logit Models. - Xi Chen 010; Yining Wang 001; Yuan Zhou 007 (CoRR, 2018)

Efficient Load Sampling for Worst-Case Structural Analysis Under Force Location Uncertainty. - Yining Wang 001; Erva Ulu; Aarti Singh; Levent Burak Kara (CoRR, 2018)

A note on a tight lower bound for capacitated MNL-bandit assortment selection models. - Xi Chen 010; Yining Wang 001 (Oper. Res. Lett., 2018)

Spectral Learning for Supervised Topic Models. - Yong Ren; Yining Wang 001; Jun Zhu 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2018)

Tight Regret Bounds for Infinite-armed Linear Contextual Bandits. - Yingkai Li; Yining Wang 001; Yuan Zhou 007 (CoRR, 2019)

√n-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank. - Kefan Dong; Jian Peng 001; Yining Wang 001; Yuan Zhou 007 (CoRR, 2019)

Technical Note - Nonstationary Stochastic Optimization Under Lp, q-Variation Measures. - Xi Chen 010; Yining Wang 001; Yu-Xiang Wang 003 (Oper. Res., 2019)

Rate optimal estimation and confidence intervals for high-dimensional regression with missing covariates. - Yining Wang 001; Jialei Wang; Sivaraman Balakrishnan; Aarti Singh (J. Multivar. Anal., 2019)

Optimization of Smooth Functions With Noisy Observations: Local Minimax Rates. - Yining Wang 001; Sivaraman Balakrishnan; Aarti Singh (IEEE Trans. Inf. Theory, 2019)

A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data. - Yining Wang 001; Yu-Xiang Wang 003; Aarti Singh (IEEE Trans. Inf. Theory, 2019)

Selective Data Acquisition in Learning and Decision Making Problems. - Yining Wang 001 (2019)

Root-n-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank. - Kefan Dong; Jian Peng 001; Yining Wang 001; Yuan Zhou 007 (COLT, 2020)

Uncertainty Quantification for Demand Prediction in Contextual Dynamic Pricing. - Xi Chen 010; Yining Wang 001 (CoRR, 2020)

Technical Note - Data-Based Dynamic Pricing and Inventory Control with Censored Demand and Limited Price Changes. - Boxiao Chen; Xiuli Chao; Yining Wang 001 (Oper. Res., 2020)

Dynamic Assortment Optimization with Changing Contextual Information. - Xi Chen 010; Yining Wang 001; Yuan Zhou 007 (J. Mach. Learn. Res., 2020)

Tight Regret Bounds for Infinite-armed Linear Contextual Bandits. - Yingkai Li; Yining Wang 001; Xi Chen 010; Yuan Zhou 007 (AISTATS, 2021)

Smooth Bandit Optimization: Generalization to Holder Space. - Yusha Liu; Yining Wang 001; Aarti Singh (AISTATS, 2021)

Optimism in Reinforcement Learning with Generalized Linear Function Approximation. - Yining Wang 001; Ruosong Wang; Simon Shaolei Du; Akshay Krishnamurthy (ICLR, 2021)

Near-Linear Time Local Polynomial Nonparametric Estimation with Box Kernels. - Yining Wang 001; Yi Wu 013; Simon S. Du (INFORMS J. Comput., 2021)

Multimodal Dynamic Pricing. - Yining Wang 001; Boxiao Chen; David Simchi-Levi (Manag. Sci., 2021)

Optimal Policy for Dynamic Assortment Planning Under Multinomial Logit Models. - Xi Chen 010; Yining Wang 001; Yuan Zhou 007 (Math. Oper. Res., 2021)

Near-optimal discrete optimization for experimental design: a regret minimization approach. - Zeyuan Allen-Zhu; Yuanzhi Li; Aarti Singh; Yining Wang 001 (Math. Program., 2021)

Fairness-aware Network Revenue Management with Demand Learning. - Xi Chen 010; Jiameng Lyu; Yining Wang 001; Yuan Zhou 007 (CoRR, 2022)

Privacy-Preserving Dynamic Personalized Pricing with Demand Learning. - Xi Chen 010; David Simchi-Levi; Yining Wang 001 (Manag. Sci., 2022)

Dynamic Pricing and Inventory Control with Fixed Ordering Cost and Incomplete Demand Information. - Boxiao Chen; David Simchi-Levi; Yining Wang 001; Yuan Zhou 007 (Manag. Sci., 2022)

Constant Regret Resolving Heuristics for Price-Based Revenue Management. - Yining Wang 001; He Wang 009 (Oper. Res., 2022)

Utility Fairness in Contextual Dynamic Pricing with Demand Learning. - Xi Chen 010; David Simchi-Levi; Yining Wang 001 (CoRR, 2023)

Differential Privacy in Personalized Pricing with Nonparametric Demand Models. - Xi Chen 010; Sentao Miao; Yining Wang 001 (Oper. Res., 2023)

Active Learning for Contextual Search with Binary Feedback. - Xi Chen 010; Quanquan Liu; Yining Wang 001 (Manag. Sci., 2023)

Robust Dynamic Pricing with Demand Learning in the Presence of Outlier Customers. - Xi Chen 010; Yining Wang 001 (Oper. Res., 2023)

On the Optimal Regret of Locally Private Linear Contextual Bandit. - Jiachun Li; David Simchi-Levi; Yining Wang 001 (CoRR, 2024)

Robust Dynamic Assortment Optimization in the Presence of Outlier Customers. - Xi Chen 010; Akshay Krishnamurthy; Yining Wang 001 (Oper. Res., 2024)

Pricing and Positioning of Horizontally Differentiated Products with Incomplete Demand Information. - Arnoud V. den Boer; Boxiao Chen; Yining Wang 001 (Oper. Res., 2024)

Optimal Policies for Dynamic Pricing and Inventory Control with Nonparametric Censored Demands. - Boxiao Chen; Yining Wang 001; Yuan Zhou 007 (Manag. Sci., 2024)

Nearly Minimax-Optimal Regret for Linearly Parameterized Bandits. - Yingkai Li; Yining Wang 001; Yuan Zhou 007 (IEEE Trans. Inf. Theory, 2024)

Technical Note - On Adaptivity in Nonstationary Stochastic Optimization with Bandit Feedback. - Yining Wang 001 (Oper. Res., 2025)