AmirEmad Ghassami

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 46

Top Topics

Measurement Error

Causal Structure

Latent Variables

Structure Learning

Top Venues

Publications

Yuqin Yang, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, AmirEmad Ghassami
Causal Discovery in Linear Models with Unobserved Variables and Measurement Error. CoRR (2024)
Zixiao Wang, AmirEmad Ghassami, Ilya Shpitser
Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach. CoRR (2023)
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 (2022)
Ehsan Mokhtarian, Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models. CoRR (2022)
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)
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)
Yuqin Yang, Mohamed S. Nafea, AmirEmad Ghassami, Negar Kiyavash
Causal Discovery in Linear Structural Causal Models with Deterministic Relations. CLeaR (2022)
AmirEmad Ghassami, Ilya Shpitser
Partially Intervenable Causal Models. CoRR (2021)
Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias. NeurIPS (2021)
Yuqin Yang, Mohamed S. Nafea, AmirEmad Ghassami, Negar Kiyavash
Causal Discovery in Linear Structural Causal Models with Deterministic Relations. CoRR (2021)
AmirEmad Ghassami, Numair Sani, Yizhen Xu, Ilya Shpitser
Multiply Robust Causal Mediation Analysis with Continuous Treatments. CoRR (2021)
AmirEmad Ghassami, Andrew Ying, Ilya Shpitser, Eric Tchetgen Tchetgen
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals. CoRR (2021)
Ehsan Mokhtarian, Sina Akbari, AmirEmad Ghassami, Negar Kiyavash
A Recursive Markov Boundary-Based Approach to Causal Structure Learning. CD@KDD (2021)
Sajad Khodadadian, AmirEmad Ghassami, Negar Kiyavash
Impact of Data Processing on Fairness in Supervised Learning. ISIT (2021)
Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias. CoRR (2021)
Sajad Khodadadian, Mohamed S. Nafea, AmirEmad Ghassami, Negar Kiyavash
Information Theoretic Measures for Fairness-aware Feature Selection. CoRR (2021)
Sajad Khodadadian, AmirEmad Ghassami, Negar Kiyavash
Impact of Data Processing on Fairness in Supervised Learning. CoRR (2021)
Ehsan Mokhtarian, Sina Akbari, AmirEmad Ghassami, Negar Kiyavash
A Recursive Markov Blanket-Based Approach to Causal Structure Learning. CoRR (2020)
Ignavier Ng, AmirEmad Ghassami, Kun Zhang
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs. NeurIPS (2020)
Alan Yang, AmirEmad Ghassami, Maxim Raginsky, Negar Kiyavash, Elyse Rosenbaum
Model-Augmented Conditional Mutual Information Estimation for Feature Selection. UAI (2020)
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 (2020)
Ignavier Ng, AmirEmad Ghassami, Kun Zhang
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs. CoRR (2020)
AmirEmad Ghassami, Alan Yang, Negar Kiyavash, Kun Zhang
Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs. ICML (2020)
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash
Interventional Experiment Design for Causal Structure Learning. CoRR (2019)
Alan Yang, AmirEmad Ghassami, Maxim Raginsky, Negar Kiyavash, Elyse Rosenbaum
Model-Augmented Nearest-Neighbor Estimation of Conditional Mutual Information for Feature Selection. CoRR (2019)
Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash, Kun Zhang
Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables. CoRR (2019)
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang
Counting and Sampling from Markov Equivalent DAGs Using Clique Trees. AAAI (2019)
AmirEmad Ghassami, Kun Zhang, Negar Kiyavash
Characterizing Distribution Equivalence for Cyclic and Acyclic Directed Graphs. CoRR (2019)
Chien-Ying Chen, Monowar Hasan, AmirEmad Ghassami, Sibin Mohan, Negar Kiyavash
REORDER: Securing Dynamic-Priority Real-Time Systems Using Schedule Obfuscation. CoRR (2018)
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash
Counting and Uniform Sampling from Markov Equivalent DAGs. CoRR (2018)
AmirEmad Ghassami, Sajad Khodadadian, Negar Kiyavash
Fairness in Supervised Learning: An Information Theoretic Approach. ISIT (2018)
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Elias Bareinboim
Budgeted Experiment Design for Causal Structure Learning. ICML (2018)
AmirEmad Ghassami, Negar Kiyavash
A Covert Queueing Channel in FCFS Schedulers. IEEE Trans. Inf. Forensics Secur. 13 (6) (2018)
AmirEmad Ghassami, Negar Kiyavash, Biwei Huang, Kun Zhang
Multi-domain Causal Structure Learning in Linear Systems. NeurIPS (2018)
AmirEmad Ghassami, Sajad Khodadadian, Negar Kiyavash
Fairness in Supervised Learning: An Information Theoretic Approach. CoRR (2018)
AmirEmad Ghassami, Negar Kiyavash
A Covert Queueing Channel in FCFS Schedulers. CoRR (2017)
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash
Optimal Experiment Design for Causal Discovery from Fixed Number of Experiments. CoRR (2017)
AmirEmad Ghassami, Negar Kiyavash
Interaction Information for Causal Inference: The Case of Directed Triangle. CoRR (2017)
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang
Learning Causal Structures Using Regression Invariance. CoRR (2017)
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang
Learning Causal Structures Using Regression Invariance. NIPS (2017)
AmirEmad Ghassami, Ali Yekkehkhany, Negar Kiyavash, Yi Lu
A Covert Queueing Channel in Round Robin Schedulers. CoRR (2017)
AmirEmad Ghassami, Negar Kiyavash
Interaction information for causal inference: The case of directed triangle. ISIT (2017)
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Elias Bareinboim
Budgeted Experiment Design for Causal Structure Learning. CoRR (2017)
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 (2017)
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)
AmirEmad Ghassami, Daniel F. Cullina, Negar Kiyavash
Message partitioning and limited auxiliary randomness: Alternatives to Honey Encryption. ISIT (2016)
AmirEmad Ghassami, Xun Gong, Negar Kiyavash
Capacity limit of queueing timing channel in shared FCFS schedulers. ISIT (2015)