Ordered multiplicity lists for eigenvalues of symmetric matrices whose graph is a linear tree. - Charles R. Johnson; Andrew A. Li; Andrew J. Walker (Discret. Math., 2014)

Approximate blocking probabilities in loss models with independence and distribution assumptions relaxed. - Andrew A. Li; Ward Whitt (Perform. Evaluation, 2014)

Optimal Recovery of Tensor Slices. - Vivek F. Farias; Andrew A. Li (AISTATS, 2017)

Learning Preferences with Side Information. - Vivek F. Farias; Andrew A. Li (Manag. Sci., 2019)

Optimizing Offer Sets in Sub-Linear Time. - Vivek F. Farias; Andrew A. Li; Deeksha Sinha (EC, 2020)

Solving the Phantom Inventory Problem: Near-optimal Entry-wise Anomaly Detection. - Vivek F. Farias; Andrew A. Li; Tianyi Peng (CoRR, 2020)

Causal Inference with Selectively Deconfounded Data. - Kyra Gan; Andrew A. Li; Zachary Chase Lipton; Sridhar R. Tayur (AISTATS, 2021)

Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise. - Vivek F. Farias; Andrew A. Li; Tianyi Peng (ICML, 2021)

Learning Treatment Effects in Panels with General Intervention Patterns. - Vivek F. Farias; Andrew A. Li; Tianyi Peng (NeurIPS, 2021)

Greedy Approximation Algorithms for Active Sequential Hypothesis Testing. - Kyra Gan; Su Jia; Andrew A. Li (NeurIPS, 2021)

Approximation Algorithms for Active Sequential Hypothesis Testing. - Kyra Gan; Su Jia; Andrew A. Li (CoRR, 2021)

Uncertainty Quantification for Low-Rank Matrix Completion with Heterogeneous and Sub-Exponential Noise. - Vivek F. Farias; Andrew A. Li; Tianyi Peng (AISTATS, 2022)

Markovian Interference in Experiments. - Vivek F. Farias; Andrew A. Li; Tianyi Peng; Andrew Zheng (NeurIPS, 2022)

Dynamic Pricing with Monotonicity Constraint under Unknown Parametric Demand Model. - Su Jia; Andrew A. Li; R. Ravi 001 (NeurIPS, 2022)

Short-lived High-volume Bandits. - Su Jia; Nishant Oli; Ian Anderson 005; Paul Duff; Andrew A. Li; R. Ravi 001 (ICML, 2023)

Modeling Choice via Self-Attention. - Joohwan Ko; Andrew A. Li (CoRR, 2023)

Markdown Pricing Under an Unknown Parametric Demand Model. - Su Jia; Andrew A. Li; R. Ravi 001 (CoRR, 2023)

Short-lived High-volume Multi-A(rmed)/B(andits) Testing. - Su Jia; Andrew A. Li; R. Ravi 001; Nishant Oli; Paul Duff; Ian Anderson 005 (CoRR, 2023)

Best of Many in Both Worlds: Online Resource Allocation with Predictions under Unknown Arrival Model. - Lin An; Andrew A. Li; Benjamin Moseley; Gabriel Visotsky (CoRR, 2024)

Fixing Inventory Inaccuracies at Scale. - Vivek F. Farias; Andrew A. Li; Tianyi Peng (Manuf. Serv. Oper. Manag., 2024)

The Nonstationary Newsvendor with (and Without) Predictions. - Lin An; Andrew A. Li; Benjamin Moseley; R. Ravi 001 (Manuf. Serv. Oper. Manag., 2025)

Multi-Armed Bandits with Endogenous Learning Curves: An Application to Split Liver Transplantation. - Yanhan (Savannah) Tang; Andrew A. Li; Alan Scheller-Wolf; Sridhar Tayur (Manuf. Serv. Oper. Manag., 2025)

Real-Time Personalization with Simple Transformers. - Lin An; Andrew A. Li; Vaisnavi Nemala; Gabriel Visotsky (CoRR, 2025)