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ORCIDSina Akbari
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2020 – today
- 2024
[c9]Sina Akbari, Negar Kiyavash:
Triple Changes Estimator for Targeted Policies. ICML 2024- [i10]Ehsan Mokhtarian
, Sepehr Elahi, Sina Akbari, Negar Kiyavash:
Recursive Causal Discovery. CoRR abs/2403.09300 (2024) - [i9]Sepehr Elahi, Sina Akbari, Jalal Etesami, Negar Kiyavash, Patrick Thiran:
Fast Proxy Experiment Design for Causal Effect Identification. CoRR abs/2407.05330 (2024) - 2023
- [j2]Sina Akbari, Adolfo R. Escobedo:
Approximate Condorcet Partitioning: Solving large-scale rank aggregation problems. Comput. Oper. Res. 153: 106164 (2023) - [j1]Matthew James Vowels, Sina Akbari, Necati Cihan Camgöz, Richard Bowden:
A Free Lunch with Influence Functions? An Empirical Evaluation of Influence Functions for Average Treatment Effect Estimation. Trans. Mach. Learn. Res. 2023 (2023) - [c8]Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash:
Causal Effect Identification in Uncertain Causal Networks. NeurIPS 2023 - [c7]Fateme Jamshidi, Sina Akbari, Negar Kiyavash:
Causal Imitability Under Context-Specific Independence Relations. NeurIPS 2023 - [i8]Sina Akbari, Luca Ganassali, Negar Kiyavash:
Learning Causal Graphs via Monotone Triangular Transport Maps. CoRR abs/2305.18210 (2023) - [i7]Fateme Jamshidi, Sina Akbari, Negar Kiyavash:
Causal Imitability Under Context-Specific Independence Relations. CoRR abs/2306.00585 (2023) - 2022
- [c6]Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash:
Learning Bayesian Networks in the Presence of Structural Side Information. AAAI 2022: 7814-7822 - [c5]Sina Akbari, Jalal Etesami, Negar Kiyavash:
Minimum Cost Intervention Design for Causal Effect Identification. ICML 2022: 258-289 - [c4]Sina Akbari, Adolfo R. Escobedo:
Top-k List Aggregation: Mathematical Formulations and Polyhedral Comparisons. ISCO 2022: 51-63 - [i6]Matthew J. Vowels, Sina Akbari, Jalal Etesami, Necati Cihan Camgöz, Richard Bowden:
A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statistics. CoRR abs/2202.09096 (2022) - [i5]Sina Akbari, Jalal Etesami, Negar Kiyavash:
Minimum Cost Intervention Design for Causal Effect Identification. CoRR abs/2205.02232 (2022) - [i4]Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash:
Causal Discovery in Probabilistic Networks with an Identifiable Causal Effect. CoRR abs/2208.04627 (2022) - 2021
- [c3]Ehsan Mokhtarian, Sina Akbari, AmirEmad Ghassami, Negar Kiyavash:
A Recursive Markov Boundary-Based Approach to Causal Structure Learning. CD@KDD 2021: 26-54 - [c2]Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash:
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias. NeurIPS 2021: 10119-10130 - [c1]Sina Akbari, Adolfo R. Escobedo:
Lower Bounds on Kemeny Rank Aggregation with Non-Strict Rankings. SSCI 2021: 1-8 - [i3]Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash:
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias. CoRR abs/2110.12036 (2021) - [i2]Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash:
Learning Bayesian Networks in the Presence of Structural Side Information. CoRR abs/2112.10884 (2021) - 2020
- [i1]Ehsan Mokhtarian, Sina Akbari, AmirEmad Ghassami, Negar Kiyavash:
A Recursive Markov Blanket-Based Approach to Causal Structure Learning. CoRR abs/2010.04992 (2020)
Coauthor Index
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