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Andrew A. Li
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2020 – today
- 2024
- [j4]Vivek F. Farias, Andrew A. Li, Tianyi Peng
:
Fixing Inventory Inaccuracies at Scale. Manuf. Serv. Oper. Manag. 26(3): 1102-1118 (2024) - [i11]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 abs/2402.13530 (2024) - 2023
- [c10]Su Jia, Nishant Oli, Ian Anderson, Paul Duff, Andrew A. Li, R. Ravi:
Short-lived High-volume Bandits. ICML 2023: 14902-14929 - [i10]Joohwan Ko, Andrew A. Li:
Modeling Choice via Self-Attention. CoRR abs/2311.07607 (2023) - [i9]Su Jia, Andrew A. Li, R. Ravi:
Markdown Pricing Under an Unknown Parametric Demand Model. CoRR abs/2312.15286 (2023) - [i8]Su Jia, Andrew A. Li, R. Ravi, Nishant Oli, Paul Duff, Ian Anderson:
Short-lived High-volume Multi-A(rmed)/B(andits) Testing. CoRR abs/2312.15356 (2023) - 2022
- [c9]Vivek F. Farias, Andrew A. Li, Tianyi Peng:
Uncertainty Quantification for Low-Rank Matrix Completion with Heterogeneous and Sub-Exponential Noise. AISTATS 2022: 1179-1189 - [c8]Vivek F. Farias, Andrew A. Li, Tianyi Peng, Andrew Zheng:
Markovian Interference in Experiments. NeurIPS 2022 - [c7]Su Jia, Andrew A. Li, R. Ravi:
Dynamic Pricing with Monotonicity Constraint under Unknown Parametric Demand Model. NeurIPS 2022 - [i7]Vivek F. Farias, Andrew A. Li, Tianyi Peng, Andrew Zheng:
Markovian Interference in Experiments. CoRR abs/2206.02371 (2022) - 2021
- [c6]Kyra Gan, Andrew A. Li, Zachary Chase Lipton, Sridhar R. Tayur:
Causal Inference with Selectively Deconfounded Data. AISTATS 2021: 2791-2799 - [c5]Vivek F. Farias, Andrew A. Li, Tianyi Peng:
Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise. ICML 2021: 3154-3163 - [c4]Kyra Gan, Su Jia, Andrew A. Li:
Greedy Approximation Algorithms for Active Sequential Hypothesis Testing. NeurIPS 2021: 5012-5024 - [c3]Vivek F. Farias, Andrew A. Li, Tianyi Peng:
Learning Treatment Effects in Panels with General Intervention Patterns. NeurIPS 2021: 14001-14013 - [i6]Kyra Gan, Su Jia, Andrew A. Li:
Approximation Algorithms for Active Sequential Hypothesis Testing. CoRR abs/2103.04250 (2021) - [i5]Vivek F. Farias, Andrew A. Li, Tianyi Peng:
Learning Treatment Effects in Panels with General Intervention Patterns. CoRR abs/2106.02780 (2021) - [i4]Vivek F. Farias, Andrew A. Li, Tianyi Peng:
Uncertainty Quantification For Low-Rank Matrix Completion With Heterogeneous and Sub-Exponential Noise. CoRR abs/2110.12046 (2021) - 2020
- [c2]Vivek F. Farias, Andrew A. Li, Deeksha Sinha:
Optimizing Offer Sets in Sub-Linear Time. EC 2020: 639-640 - [i3]Kyra Gan, Andrew A. Li, Zachary C. Lipton, Sridhar R. Tayur:
Causal Inference With Selectively-Deconfounded Data. CoRR abs/2002.11096 (2020) - [i2]Vivek F. Farias, Andrew A. Li, Tianyi Peng:
Solving the Phantom Inventory Problem: Near-optimal Entry-wise Anomaly Detection. CoRR abs/2006.13126 (2020) - [i1]Vivek F. Farias, Andrew A. Li, Deeksha Sinha:
Optimizing Offer Sets in Sub-Linear Time. CoRR abs/2011.08606 (2020)
2010 – 2019
- 2019
- [j3]Vivek F. Farias
Learning Preferences with Side Information. Manag. Sci. 65(7): 3131-3149 (2019) - 2017
- [c1]Vivek F. Farias, Andrew A. Li:
Optimal Recovery of Tensor Slices. AISTATS 2017: 1394-1402 - 2014
- [j2]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: 39-55 (2014) - [j1]Andrew A. Li, Ward Whitt:
Approximate blocking probabilities in loss models with independence and distribution assumptions relaxed. Perform. Evaluation 80: 82-101 (2014)
Coauthor Index
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