AmirEmad Ghassami

51 papers A* 9A 3B 5Journal 30Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Causal Imitation Learning Under Measurement Error and Distribution Shift. CoRR Shi Bo, AmirEmad Ghassami
2024	A	`conf`	A General Identification Algorithm For Data Fusion Problems Under Systematic Selection. UAI Jaron Jia Rong Lee, AmirEmad Ghassami, Ilya Shpitser
2024	J	`jnl`	Causal Discovery in Linear Models with Unobserved Variables and Measurement Error. CoRR Yuqin Yang, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, AmirEmad Ghassami
2024	A*	`conf`	Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach. ICML Zixiao Wang, AmirEmad Ghassami, Ilya Shpitser
2023	J	`jnl`	A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models. J. Mach. Learn. Res. Ehsan Mokhtarian, Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash
2023	J	`jnl`	Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach. CoRR Zixiao Wang, AmirEmad Ghassami, Ilya Shpitser
2022	J	`jnl`	A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models. CoRR Ehsan Mokhtarian, Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash
2022	A*	`conf`	Causal Discovery in Linear Latent Variable Models Subject to Measurement Error. NeurIPS Yuqin Yang, AmirEmad Ghassami, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, Ilya Shpitser
2022	J	`jnl`	Causal Discovery in Linear Latent Variable Models Subject to Measurement Error. CoRR Yuqin Yang, AmirEmad Ghassami, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, Ilya Shpitser
2022	—	`conf`	Causal Discovery in Linear Structural Causal Models with Deterministic Relations. CLeaR Yuqin Yang, Mohamed S. Nafea, AmirEmad Ghassami, Negar Kiyavash
2022	A	`conf`	Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference. AISTATS AmirEmad Ghassami, Andrew Ying, Ilya Shpitser, Eric Tchetgen Tchetgen
2021	—	`conf`	A Recursive Markov Boundary-Based Approach to Causal Structure Learning. CD@KDD Ehsan Mokhtarian, Sina Akbari, AmirEmad Ghassami, Negar Kiyavash
2021	J	`jnl`	Causal Discovery in Linear Structural Causal Models with Deterministic Relations. CoRR Yuqin Yang, Mohamed S. Nafea, AmirEmad Ghassami, Negar Kiyavash
2021	B	`conf`	Impact of Data Processing on Fairness in Supervised Learning. ISIT Sajad Khodadadian, AmirEmad Ghassami, Negar Kiyavash
2021	J	`jnl`	Impact of Data Processing on Fairness in Supervised Learning. CoRR Sajad Khodadadian, AmirEmad Ghassami, Negar Kiyavash
2021	J	`jnl`	Information Theoretic Measures for Fairness-aware Feature Selection. CoRR Sajad Khodadadian, Mohamed S. Nafea, AmirEmad Ghassami, Negar Kiyavash
2021	J	`jnl`	Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals. CoRR AmirEmad Ghassami, Andrew Ying, Ilya Shpitser, Eric Tchetgen Tchetgen
2021	J	`jnl`	Multiply Robust Causal Mediation Analysis with Continuous Treatments. CoRR AmirEmad Ghassami, Numair Sani, Yizhen Xu, Ilya Shpitser
2021	A*	`conf`	Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias. NeurIPS Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash
2021	J	`jnl`	Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias. CoRR Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash
2020	J	`jnl`	A Recursive Markov Blanket-Based Approach to Causal Structure Learning. CoRR Ehsan Mokhtarian, Sina Akbari, AmirEmad Ghassami, Negar Kiyavash
2020	—	`—`	Causal discovery beyond Markov equivalence AmirEmad Ghassami
2020	A*	`conf`	Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs. ICML AmirEmad Ghassami, Alan Yang, Negar Kiyavash, Kun Zhang
2020	J	`jnl`	Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables. J. Mach. Learn. Res. Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash, Kun Zhang
2020	A	`conf`	Model-Augmented Conditional Mutual Information Estimation for Feature Selection. UAI Alan Yang, AmirEmad Ghassami, Maxim Raginsky, Negar Kiyavash, Elyse Rosenbaum
2020	A*	`conf`	On the Role of Sparsity and DAG Constraints for Learning Linear DAGs. NeurIPS Ignavier Ng, AmirEmad Ghassami, Kun Zhang
2020	J	`jnl`	On the Role of Sparsity and DAG Constraints for Learning Linear DAGs. CoRR Ignavier Ng, AmirEmad Ghassami, Kun Zhang
2019	J	`jnl`	Characterizing Distribution Equivalence for Cyclic and Acyclic Directed Graphs. CoRR AmirEmad Ghassami, Kun Zhang, Negar Kiyavash
2019	A*	`conf`	Counting and Sampling from Markov Equivalent DAGs Using Clique Trees. AAAI AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang
2019	J	`jnl`	Interventional Experiment Design for Causal Structure Learning. CoRR AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash
2019	J	`jnl`	Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables. CoRR Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash, Kun Zhang
2019	J	`jnl`	Model-Augmented Nearest-Neighbor Estimation of Conditional Mutual Information for Feature Selection. CoRR Alan Yang, AmirEmad Ghassami, Maxim Raginsky, Negar Kiyavash, Elyse Rosenbaum
2018	J	`jnl`	A Covert Queueing Channel in FCFS Schedulers. IEEE Trans. Inf. Forensics Secur. AmirEmad Ghassami, Negar Kiyavash
2018	A*	`conf`	Budgeted Experiment Design for Causal Structure Learning. ICML AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Elias Bareinboim
2018	J	`jnl`	Counting and Uniform Sampling from Markov Equivalent DAGs. CoRR AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash
2018	B	`conf`	Fairness in Supervised Learning: An Information Theoretic Approach. ISIT AmirEmad Ghassami, Sajad Khodadadian, Negar Kiyavash
2018	J	`jnl`	Fairness in Supervised Learning: An Information Theoretic Approach. CoRR AmirEmad Ghassami, Sajad Khodadadian, Negar Kiyavash
2018	A*	`conf`	Multi-domain Causal Structure Learning in Linear Systems. NeurIPS AmirEmad Ghassami, Negar Kiyavash, Biwei Huang, Kun Zhang
2018	J	`jnl`	REORDER: Securing Dynamic-Priority Real-Time Systems Using Schedule Obfuscation. CoRR Chien-Ying Chen, Monowar Hasan, AmirEmad Ghassami, Sibin Mohan, Negar Kiyavash
2017	J	`jnl`	A Covert Queueing Channel in FCFS Schedulers. CoRR AmirEmad Ghassami, Negar Kiyavash
2017	J	`jnl`	A Covert Queueing Channel in Round Robin Schedulers. CoRR AmirEmad Ghassami, Ali Yekkehkhany, Negar Kiyavash, Yi Lu
2017	J	`jnl`	A Reconnaissance Attack Mechanism for Fixed-Priority Real-Time Systems. CoRR Chien-Ying Chen, AmirEmad Ghassami, Sibin Mohan, Negar Kiyavash, Rakesh B. Bobba, Rodolfo Pellizzoni, Man-Ki Yoon
2017	J	`jnl`	Budgeted Experiment Design for Causal Structure Learning. CoRR AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Elias Bareinboim
2017	J	`jnl`	Interaction Information for Causal Inference: The Case of Directed Triangle. CoRR AmirEmad Ghassami, Negar Kiyavash
2017	B	`conf`	Interaction information for causal inference: The case of directed triangle. ISIT AmirEmad Ghassami, Negar Kiyavash
2017	—	`conf`	Learning Causal Structures Using Regression Invariance. NIPS AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang
2017	J	`jnl`	Learning Causal Structures Using Regression Invariance. CoRR AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang
2017	J	`jnl`	Optimal Experiment Design for Causal Discovery from Fixed Number of Experiments. CoRR AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash
2016	B	`conf`	Message partitioning and limited auxiliary randomness: Alternatives to Honey Encryption. ISIT AmirEmad Ghassami, Daniel F. Cullina, Negar Kiyavash
2016	A*	`conf`	Sneak-Peek: High speed covert channels in data center networks. INFOCOM Rashid Tahir, Mohammad Taha Khan, Xun Gong, Adnan Ahmed, AmirEmad Ghassami, Hasanat Kazmi, Matthew Caesar, Fareed Zaffar, Negar Kiyavash
2015	B	`conf`	Capacity limit of queueing timing channel in shared FCFS schedulers. ISIT AmirEmad Ghassami, Xun Gong, Negar Kiyavash