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ORCIDAng Li 0009
Person information
- affiliation: Florida State University, Department of Computer Science, Tallahassee, FL, USA
- affiliation (former, PhD 2021): University of California, Los Angeles, Department of Computer Science, CA, USA
Other persons with the same name
- Ang Li — disambiguation page
- Ang Li 0001 — University of Maryland, College Park, MD, USA
- Ang Li 0002 — Duke University, Durham, NC, USA
- Ang Li 0003
![[0000-0001-8235-7596]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-8235-7596")
— Xi'an Jiaotong University, Faculty of Electronic and Information Engineering, Shaanxi, China (and 3 more) - Ang Li 0004 — Beijing Forestry University, Department of Psychology, China (and 2 more)
- Ang Li 0005 — Duke University, Department of Electrical and Computer Engineering, Durham, NC, USA (and 1 more)
- Ang Li 0006 — Pacific Northwest National Laboratory, Richland, WA, USA
- Ang Li 0007 (aka: Ang Leon Li) — University of Queensland, Brisbane, QLD, Australia
- Ang Li 0008 — University of Melbourne, School of Computing and Information Systems, Parkville, Victoria, Australia
- Ang Li 0010 — Stanford University, CA, USA
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2020 – today
- 2024
[c9]Ang Li, Judea Pearl:
Probabilities of Causation with Nonbinary Treatment and Effect. AAAI 2024: 20465-20472- [c8]Ang Li, Judea Pearl:
Unit Selection with Nonbinary Treatment and Effect. AAAI 2024: 20473-20480 - 2023
- [c7]Ang Li, Judea Pearl:
Probabilities of Causation: Role of Observational Data. AISTATS 2023: 10012-10027 - [i11]Ang Li, Scott Mueller, Judea Pearl:
Epsilon-Identifiability of Causal Quantities. CoRR abs/2301.12022 (2023) - 2022
- [c6]Ang Li, Judea Pearl:
Unit Selection with Causal Diagram. AAAI 2022: 5765-5772 - [c5]Ang Li, Judea Pearl:
Bounds on Causal Effects and Application to High Dimensional Data. AAAI 2022: 5773-5780 - [c4]Scott Mueller, Ang Li, Judea Pearl:
Causes of Effects: Learning Individual Responses from Population Data. IJCAI 2022: 2712-2718 - [i10]Ang Li, Judea Pearl:
Probabilities of Causation with Nonbinary Treatment and Effect. CoRR abs/2208.09568 (2022) - [i9]Ang Li, Judea Pearl:
Unit Selection with Nonbinary Treatment and Effect. CoRR abs/2208.09569 (2022) - [i8]Ang Li, Ruirui Mao, Judea Pearl:
Probabilities of Causation: Adequate Size of Experimental and Observational Samples. CoRR abs/2210.05027 (2022) - [i7]Ang Li, Judea Pearl:
Unit Selection: Case Study and Comparison with A/B Test Heuristic. CoRR abs/2210.05030 (2022) - [i6]Ang Li, Song Jiang, Yizhou Sun, Judea Pearl:
Unit Selection: Learning Benefit Function from Finite Population Data. CoRR abs/2210.08203 (2022) - [i5]Ang Li, Song Jiang, Yizhou Sun, Judea Pearl:
Learning Probabilities of Causation from Finite Population Data. CoRR abs/2210.08453 (2022) - [i4]Ang Li, Judea Pearl:
Probabilities of Causation: Role of Observational Data. CoRR abs/2210.08874 (2022) - 2021
- [i3]Scott Mueller, Ang Li, Judea Pearl:
Causes of Effects: Learning individual responses from population data. CoRR abs/2104.13730 (2021) - [i2]Ang Li, Judea Pearl:
Bounds on Causal Effects and Application to High Dimensional Data. CoRR abs/2106.12121 (2021) - [i1]Ang Li, Judea Pearl:
Unit Selection with Causal Diagram. CoRR abs/2109.07556 (2021) - 2020
- [c3]Ang Li, Suming J. Chen, Jingzheng Qin, Zhen Qin:
Training Machine Learning Models With Causal Logic. WWW (Companion Volume) 2020: 557-561
2010 – 2019
- 2019
- [c2]Ang Li, Judea Pearl:
Unit Selection Based on Counterfactual Logic. IJCAI 2019: 1793-1799 - 2013
- [c1]Ang Li, Paul R. Schrater:
Efficient Learning in Linearly Solvable MDP Models. IJCAI 2013: 248-253
Coauthor Index
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last updated on 2024-04-26 20:09 CEST by the dblp team
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