Iterative Collaborative Filtering for Sparse Noisy Tensor Estimation. - Devavrat Shah; Christina Lee Yu (ISIT, 2019)

Nonparametric Contextual Bandits in Metric Spaces with Unknown Metric. - Nirandika Wanigasekara; Christina Lee Yu (NeurIPS, 2019)

Nonparametric Contextual Bandits in an Unknown Metric Space. - Nirandika Wanigasekara; Christina Lee Yu (CoRR, 2019)

Adaptive Discretization for Episodic Reinforcement Learning in Metric Spaces. - Sean R. Sinclair; Siddhartha Banerjee; Christina Lee Yu (Proc. ACM Meas. Anal. Comput. Syst., 2019)

Adaptive Discretization for Model-Based Reinforcement Learning. - Sean R. Sinclair; Tianyu Wang; Gauri Jain; Siddhartha Banerjee; Christina Lee Yu (NeurIPS, 2020)

Tensor Estimation with Nearly Linear Samples. - Christina Lee Yu (CoRR, 2020)

Sequential Fair Allocation of Limited Resources under Stochastic Demands. - Sean R. Sinclair; Gauri Jain; Siddhartha Banerjee; Christina Lee Yu (CoRR, 2020)

Editorial. - Devavrat Shah; Guy Bresler; John C. Duchi; Po-Ling Loh; Yihong Wu 001; Christina Lee Yu (IEEE J. Sel. Areas Inf. Theory, 2020)

Nearest Neighbors for Matrix Estimation Interpreted as Blind Regression for Latent Variable Model. - Yihua Li; Devavrat Shah; Dogyoon Song; Christina Lee Yu (IEEE Trans. Inf. Theory, 2020)

Asynchronous Approximation of a Single Component of the Solution to a Linear System. - Asuman E. Ozdaglar; Devavrat Shah; Christina Lee Yu (IEEE Trans. Netw. Sci. Eng., 2020)

Nonparametric Matrix Estimation with One-Sided Covariates. - Christina Lee Yu (ISIT, 2022)

Staggered Rollout Designs Enable Causal Inference Under Interference Without Network Knowledge. - Mayleen Cortez; Matthew Eichhorn; Christina Lee Yu (NeurIPS, 2022)

Sequential Fair Allocation: Achieving the Optimal Envy-Efficiency Tradeoff Curve. - Sean R. Sinclair; Siddhartha Banerjee; Christina Lee Yu (SIGMETRICS (Abstracts), 2022)

Graph Agnostic Randomized Experimental Design. - Christina Lee Yu; Edoardo M. Airoldi; Christian Borgs; Jennifer T. Chayes (CoRR, 2022)

Graph Agnostic Estimators with Staggered Rollout Designs under Network Interference. - Mayleen Cortez; Matthew Eichhorn; Christina Lee Yu (CoRR, 2022)

Exploiting neighborhood interference with low order interactions under unit randomized design. - Mayleen Cortez; Matthew Eichhorn; Christina Lee Yu (CoRR, 2022)

Artificial Replay: A Meta-Algorithm for Harnessing Historical Data in Bandits. - Siddhartha Banerjee; Sean R. Sinclair; Milind Tambe; Lily Xu; Christina Lee Yu (CoRR, 2022)

Network Synthetic Interventions: A Framework for Panel Data with Network Interference. - Anish Agarwal; Sarah H. Cen; Devavrat Shah; Christina Lee Yu (CoRR, 2022)

Tensor Completion with Nearly Linear Samples Given Weak Side Information. - Christina Lee Yu; Xumei Xi (Proc. ACM Meas. Anal. Comput. Syst., 2022)

ORSuite: Benchmarking Suite for Sequential Operations Models. - Christopher Archer; Siddhartha Banerjee; Mayleen Cortez; Carrie Rucker; Sean R. Sinclair; Max Solberg; Qiaomin Xie; Christina Lee Yu (SIGMETRICS Perform. Evaluation Rev., 2022)

Iterative Collaborative Filtering for Sparse Matrix Estimation. - Christian Borgs; Jennifer T. Chayes; Devavrat Shah; Christina Lee Yu (Oper. Res., 2022)

Entry-Specific Bounds for Low-Rank Matrix Completion under Highly Non-Uniform Sampling. - Xumei Xi; Christina Lee Yu; Yudong Chen 001 (ISIT, 2023)

Matrix Estimation for Offline Reinforcement Learning with Low-Rank Structure. - Xumei Xi; Christina Lee Yu; Yudong Chen 001 (CoRR, 2023)

Faster Rates for Switchback Experiments. - Su Jia; Sohom Bhattacharya; Nathan Kallus; Christina Lee Yu (CoRR, 2023)

Adaptive Discretization in Online Reinforcement Learning. - Sean R. Sinclair; Siddhartha Banerjee; Christina Lee Yu (Oper. Res., 2023)

Sequential Fair Allocation: Achieving the Optimal Envy-Efficiency Trade-off Curve. - Sean R. Sinclair; Gauri Jain; Siddhartha Banerjee; Christina Lee Yu (Oper. Res., 2023)

Overcoming the Long Horizon Barrier for Sample-Efficient Reinforcement Learning with Latent Low-Rank Structure. - Tyler Sam; Yudong Chen 001; Christina Lee Yu (Proc. ACM Meas. Anal. Comput. Syst., 2023)

Robust Max Entrywise Error Bounds for Tensor Estimation From Sparse Observations via Similarity-Based Collaborative Filtering. - Devavrat Shah; Christina Lee Yu (IEEE Trans. Inf. Theory, 2023)

The SMART approach to instance-optimal online learning. - Siddhartha Banerjee; Alankrita Bhatt; Christina Lee Yu (COLT, 2024)

Hierarchical Generalization Bounds for Deep Neural Networks. - Haiyun He; Christina Lee Yu; Ziv Goldfeld (ISIT, 2024)

The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure. - Tyler Sam; Yudong Chen 001; Christina Lee Yu (NeurIPS, 2024)

Information-Theoretic Generalization Bounds for Deep Neural Networks. - Haiyun He; Christina Lee Yu; Ziv Goldfeld (CoRR, 2024)

Combining Rollout Designs and Clustering for Causal Inference under Low-order Interference. - Mayleen Cortez-Rodriguez; Matthew Eichhorn; Christina Lee Yu (CoRR, 2024)

Entry-Specific Matrix Estimation under Arbitrary Sampling Patterns through the Lens of Network Flows. - Yudong Chen 001; Xumei Xi; Christina Lee Yu (CoRR, 2024)

Detection of small holes by the scale-invariant robust density-aware distance (RDAD) filtration. - Chunyin Siu; Gennady Samorodnitsky; Christina Lee Yu; Andrey Yao (J. Appl. Comput. Topol., 2024)

Analysis of Two-Stage Rollout Designs with Clustering for Causal Inference under Network Interference. - Mayleen Cortez-Rodriguez; Matthew Eichhorn; Christina Lee Yu (AISTATS, 2025)

Entry-Specific Matrix Estimation Under Arbitrary Sampling Patterns Through the Lens of Network Flows (Extended Abstract). - Yudong Chen 001; Xumei Xi; Christina Lee Yu (ITCS, 2025)