Andrew A. Li

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 23

Top Topics

Matrix Completion

Hypothesis Test

Approximation Algorithms

Top Venues

Publications

Vivek F. Farias, Andrew A. Li, Tianyi Peng
Fixing Inventory Inaccuracies at Scale. Manuf. Serv. Oper. Manag. 26 (3) (2024)
Lin An, Andrew A. Li, Benjamin Moseley, Gabriel Visotsky
Best of Many in Both Worlds: Online Resource Allocation with Predictions under Unknown Arrival Model. CoRR (2024)
Joohwan Ko, Andrew A. Li
Modeling Choice via Self-Attention. CoRR (2023)
Su Jia, Andrew A. Li, R. Ravi
Markdown Pricing Under an Unknown Parametric Demand Model. CoRR (2023)
Su Jia, Nishant Oli, Ian Anderson, Paul Duff, Andrew A. Li, R. Ravi
Short-lived High-volume Bandits. ICML (2023)
Su Jia, Andrew A. Li, R. Ravi, Nishant Oli, Paul Duff, Ian Anderson
Short-lived High-volume Multi-A(rmed)/B(andits) Testing. CoRR (2023)
Vivek F. Farias, Andrew A. Li, Tianyi Peng
Uncertainty Quantification for Low-Rank Matrix Completion with Heterogeneous and Sub-Exponential Noise. AISTATS (2022)
Su Jia, Andrew A. Li, R. Ravi
Dynamic Pricing with Monotonicity Constraint under Unknown Parametric Demand Model. NeurIPS (2022)
Vivek F. Farias, Andrew A. Li, Tianyi Peng, Andrew Zheng
Markovian Interference in Experiments. CoRR (2022)
Vivek F. Farias, Andrew A. Li, Tianyi Peng, Andrew Zheng
Markovian Interference in Experiments. NeurIPS (2022)
Vivek F. Farias, Andrew A. Li, Tianyi Peng
Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise. ICML (2021)
Vivek F. Farias, Andrew A. Li, Tianyi Peng
Uncertainty Quantification For Low-Rank Matrix Completion With Heterogeneous and Sub-Exponential Noise. CoRR (2021)
Kyra Gan, Su Jia, Andrew A. Li
Greedy Approximation Algorithms for Active Sequential Hypothesis Testing. NeurIPS (2021)
Vivek F. Farias, Andrew A. Li, Tianyi Peng
Learning Treatment Effects in Panels with General Intervention Patterns. CoRR (2021)
Kyra Gan, Su Jia, Andrew A. Li
Approximation Algorithms for Active Sequential Hypothesis Testing. CoRR (2021)
Vivek F. Farias, Andrew A. Li, Tianyi Peng
Learning Treatment Effects in Panels with General Intervention Patterns. NeurIPS (2021)
Kyra Gan, Andrew A. Li, Zachary Chase Lipton, Sridhar R. Tayur
Causal Inference with Selectively Deconfounded Data. AISTATS (2021)
Vivek F. Farias, Andrew A. Li, Tianyi Peng
Solving the Phantom Inventory Problem: Near-optimal Entry-wise Anomaly Detection. CoRR (2020)
Vivek F. Farias, Andrew A. Li, Deeksha Sinha
Optimizing Offer Sets in Sub-Linear Time. CoRR (2020)
Vivek F. Farias, Andrew A. Li, Deeksha Sinha
Optimizing Offer Sets in Sub-Linear Time. EC (2020)
Kyra Gan, Andrew A. Li, Zachary C. Lipton, Sridhar R. Tayur
Causal Inference With Selectively-Deconfounded Data. CoRR (2020)
Vivek F. Farias, Andrew A. Li
Learning Preferences with Side Information. Manag. Sci. 65 (7) (2019)
Vivek F. Farias, Andrew A. Li
Optimal Recovery of Tensor Slices. AISTATS (2017)
Andrew A. Li, Ward Whitt
Approximate blocking probabilities in loss models with independence and distribution assumptions relaxed. Perform. Evaluation 80 (2014)
Charles R. Johnson, Andrew A. Li, Andrew J. Walker
Ordered multiplicity lists for eigenvalues of symmetric matrices whose graph is a linear tree. Discret. Math. 333 (2014)