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ORCIDAmirEmad Ghassami
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2020 – today
- 2024
[c19]Zixiao Wang, AmirEmad Ghassami, Ilya Shpitser:
Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach. ICML 2024- [i26]Yuqin Yang, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, AmirEmad Ghassami:
Causal Discovery in Linear Models with Unobserved Variables and Measurement Error. CoRR abs/2407.19426 (2024) - 2023
- [j3]Ehsan Mokhtarian
, Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash:
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models. J. Mach. Learn. Res. 24: 354:1-354:31 (2023) - [i25]Zixiao Wang, AmirEmad Ghassami, Ilya Shpitser:
Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach. CoRR abs/2311.09015 (2023) - 2022
- [c18]AmirEmad Ghassami, Andrew Ying, Ilya Shpitser, Eric Tchetgen Tchetgen:
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference. AISTATS 2022: 7210-7239 - [c17]Yuqin Yang, Mohamed S. Nafea, AmirEmad Ghassami, Negar Kiyavash:
Causal Discovery in Linear Structural Causal Models with Deterministic Relations. CLeaR 2022: 944-993 - [c16]Yuqin Yang, AmirEmad Ghassami, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, Ilya Shpitser:
Causal Discovery in Linear Latent Variable Models Subject to Measurement Error. NeurIPS 2022 - [i24]Ehsan Mokhtarian, Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash:
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models. CoRR abs/2205.10083 (2022) - [i23]Yuqin Yang, AmirEmad Ghassami, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, Ilya Shpitser:
Causal Discovery in Linear Latent Variable Models Subject to Measurement Error. CoRR abs/2211.03984 (2022) - 2021
- [c15]Sajad Khodadadian, AmirEmad Ghassami, Negar Kiyavash:
Impact of Data Processing on Fairness in Supervised Learning. ISIT 2021: 2643-2648 - [c14]Ehsan Mokhtarian, Sina Akbari, AmirEmad Ghassami, Negar Kiyavash:
A Recursive Markov Boundary-Based Approach to Causal Structure Learning. CD@KDD 2021: 26-54 - [c13]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 - [i22]Sajad Khodadadian, AmirEmad Ghassami, Negar Kiyavash:
Impact of Data Processing on Fairness in Supervised Learning. CoRR abs/2102.01867 (2021) - [i21]AmirEmad Ghassami, Andrew Ying, Ilya Shpitser, Eric Tchetgen Tchetgen:
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals. CoRR abs/2104.02929 (2021) - [i20]AmirEmad Ghassami, Numair Sani, Yizhen Xu, Ilya Shpitser:
Multiply Robust Causal Mediation Analysis with Continuous Treatments. CoRR abs/2105.09254 (2021) - [i19]Sajad Khodadadian, Mohamed S. Nafea, AmirEmad Ghassami, Negar Kiyavash:
Information Theoretic Measures for Fairness-aware Feature Selection. CoRR abs/2106.00772 (2021) - [i18]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) - [i17]Yuqin Yang, Mohamed S. Nafea, AmirEmad Ghassami, Negar Kiyavash:
Causal Discovery in Linear Structural Causal Models with Deterministic Relations. CoRR abs/2111.00341 (2021) - 2020
- [b1]AmirEmad Ghassami:
Causal discovery beyond Markov equivalence. University of Illinois Urbana-Champaign, USA, 2020 - [j2]Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash, Kun Zhang:
Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables. J. Mach. Learn. Res. 21: 39:1-39:24 (2020) - [c12]AmirEmad Ghassami, Alan Yang, Negar Kiyavash, Kun Zhang:
Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs. ICML 2020: 3494-3504 - [c11]Ignavier Ng, AmirEmad Ghassami, Kun Zhang:
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs. NeurIPS 2020 - [c10]Alan Yang, AmirEmad Ghassami, Maxim Raginsky, Negar Kiyavash, Elyse Rosenbaum:
Model-Augmented Conditional Mutual Information Estimation for Feature Selection. UAI 2020: 1139-1148 - [i16]Ignavier Ng, AmirEmad Ghassami, Kun Zhang:
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs. CoRR abs/2006.10201 (2020) - [i15]Ehsan Mokhtarian, Sina Akbari, AmirEmad Ghassami, Negar Kiyavash:
A Recursive Markov Blanket-Based Approach to Causal Structure Learning. CoRR abs/2010.04992 (2020)
2010 – 2019
- 2019
- [c9]AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang:
Counting and Sampling from Markov Equivalent DAGs Using Clique Trees. AAAI 2019: 3664-3671 - [i14]Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash, Kun Zhang:
Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables. CoRR abs/1908.03932 (2019) - [i13]AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash:
Interventional Experiment Design for Causal Structure Learning. CoRR abs/1910.05651 (2019) - [i12]AmirEmad Ghassami, Kun Zhang, Negar Kiyavash:
Characterizing Distribution Equivalence for Cyclic and Acyclic Directed Graphs. CoRR abs/1910.12993 (2019) - [i11]Alan Yang, AmirEmad Ghassami, Maxim Raginsky, Negar Kiyavash, Elyse Rosenbaum:
Model-Augmented Nearest-Neighbor Estimation of Conditional Mutual Information for Feature Selection. CoRR abs/1911.04628 (2019) - 2018
- [j1]AmirEmad Ghassami, Negar Kiyavash:
A Covert Queueing Channel in FCFS Schedulers. IEEE Trans. Inf. Forensics Secur. 13(6): 1551-1563 (2018) - [c8]AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Elias Bareinboim:
Budgeted Experiment Design for Causal Structure Learning. ICML 2018: 1719-1728 - [c7]AmirEmad Ghassami, Sajad Khodadadian, Negar Kiyavash:
Fairness in Supervised Learning: An Information Theoretic Approach. ISIT 2018: 176-180 - [c6]AmirEmad Ghassami, Negar Kiyavash, Biwei Huang, Kun Zhang:
Multi-domain Causal Structure Learning in Linear Systems. NeurIPS 2018: 6269-6279 - [i10]AmirEmad Ghassami, Sajad Khodadadian, Negar Kiyavash:
Fairness in Supervised Learning: An Information Theoretic Approach. CoRR abs/1801.04378 (2018) - [i9]AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash:
Counting and Uniform Sampling from Markov Equivalent DAGs. CoRR abs/1802.01239 (2018) - [i8]Chien-Ying Chen, Monowar Hasan, AmirEmad Ghassami, Sibin Mohan, Negar Kiyavash:
REORDER: Securing Dynamic-Priority Real-Time Systems Using Schedule Obfuscation. CoRR abs/1806.01393 (2018) - 2017
- [c5]AmirEmad Ghassami, Negar Kiyavash:
Interaction information for causal inference: The case of directed triangle. ISIT 2017: 1326-1330 - [c4]AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang:
Learning Causal Structures Using Regression Invariance. NIPS 2017: 3011-3021 - [i7]AmirEmad Ghassami, Negar Kiyavash:
Interaction Information for Causal Inference: The Case of Directed Triangle. CoRR abs/1701.08868 (2017) - [i6]AmirEmad Ghassami, Ali Yekkehkhany, Negar Kiyavash, Yi Lu:
A Covert Queueing Channel in Round Robin Schedulers. CoRR abs/1701.08883 (2017) - [i5]AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash:
Optimal Experiment Design for Causal Discovery from Fixed Number of Experiments. CoRR abs/1702.08567 (2017) - [i4]Chien-Ying Chen, AmirEmad Ghassami, Sibin Mohan, Negar Kiyavash, Rakesh B. Bobba, Rodolfo Pellizzoni, Man-Ki Yoon:
A Reconnaissance Attack Mechanism for Fixed-Priority Real-Time Systems. CoRR abs/1705.02561 (2017) - [i3]AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang:
Learning Causal Structures Using Regression Invariance. CoRR abs/1705.09644 (2017) - [i2]AmirEmad Ghassami, Negar Kiyavash:
A Covert Queueing Channel in FCFS Schedulers. CoRR abs/1707.07234 (2017) - [i1]AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Elias Bareinboim:
Budgeted Experiment Design for Causal Structure Learning. CoRR abs/1709.03625 (2017) - 2016
- [c3]Rashid Tahir, Mohammad Taha Khan, Xun Gong, Adnan Ahmed, AmirEmad Ghassami, Hasanat Kazmi, Matthew Caesar, Fareed Zaffar, Negar Kiyavash:
Sneak-Peek: High speed covert channels in data center networks. INFOCOM 2016: 1-9 - [c2]AmirEmad Ghassami, Daniel F. Cullina, Negar Kiyavash:
Message partitioning and limited auxiliary randomness: Alternatives to Honey Encryption. ISIT 2016: 1371-1375 - 2015
- [c1]AmirEmad Ghassami, Xun Gong, Negar Kiyavash:
Capacity limit of queueing timing channel in shared FCFS schedulers. ISIT 2015: 789-793
Coauthor Index
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