AmirEmad Ghassami | DeepAI

DeepAI AI Chat

Featured Co-authors

Kun Zhang
106 publications
Ilya Shpitser
53 publications
Negar Kiyavash
48 publications
Eric Tchetgen Tchetgen
42 publications
Maxim Raginsky
27 publications
Saber Salehkaleybar
27 publications
Elias Bareinboim
21 publications
Andrew Ying
16 publications
Sibin Mohan
15 publications
Rakesh B. Bobba
12 publications
Ignavier Ng
9 publications

∙ 04/10/2023

Partial Identification of Causal Effects Using Proxy Variables

Proximal causal inference is a recently proposed framework for evaluatin...

0 AmirEmad Ghassami, et al. ∙

∙ 05/20/2022

A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models

We study experiment design for the unique identification of the causal g...

0 Ehsan Mokhtarian, et al. ∙

∙ 01/26/2022

Combining Experimental and Observational Data for Identification and Estimation of Long-Term Causal Effects

We consider the task of identifying and estimating the causal effect of ...

0 AmirEmad Ghassami, et al. ∙

∙ 11/04/2021

Proximal Causal Inference with Hidden Mediators: Front-Door and Related Mediation Problems

Proximal causal inference was recently proposed as a framework to identi...

0 AmirEmad Ghassami, et al. ∙

∙ 10/30/2021

Causal Discovery in Linear Structural Causal Models with Deterministic Relations

Linear structural causal models (SCMs) – in which each observed variable...

0 Yuqin Yang, et al. ∙

∙ 10/24/2021

Partially Intervenable Causal Models

Graphical causal models led to the development of complete non-parametri...

0 AmirEmad Ghassami, et al. ∙

∙ 10/22/2021

Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias

We consider the problem of learning the causal MAG of a system from obse...

0 Sina Akbari, et al. ∙

∙ 06/01/2021

Information Theoretic Measures for Fairness-aware Feature Selection

Machine learning algorithms are increasingly used for consequential deci...

0 Sajad Khodadadian, et al. ∙

∙ 05/19/2021

Multiply Robust Causal Mediation Analysis with Continuous Treatments

In many applications, researchers are interested in the direct and indir...

0 AmirEmad Ghassami, et al. ∙

∙ 04/07/2021

Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals

A moment function is called doubly robust if it is comprised of two nuis...

0 AmirEmad Ghassami, et al. ∙

∙ 02/03/2021

Impact of Data Processing on Fairness in Supervised Learning

We study the impact of pre and post processing for reducing discriminati...

0 Sajad Khodadadian, et al. ∙

∙ 10/10/2020

A Recursive Markov Blanket-Based Approach to Causal Structure Learning

One of the main approaches for causal structure learning is constraint-b...

0 Ehsan Mokhtarian, et al. ∙

∙ 06/17/2020

On the Role of Sparsity and DAG Constraints for Learning Linear DAGs

Learning graphical structure based on Directed Acyclic Graphs (DAGs) is ...

0 Ignavier Ng, et al. ∙

∙ 11/12/2019

Model-Augmented Nearest-Neighbor Estimation of Conditional Mutual Information for Feature Selection

Markov blanket feature selection, while theoretically optimal, generally...

0 Alan Yang, et al. ∙

∙ 10/28/2019

Characterizing Distribution Equivalence for Cyclic and Acyclic Directed Graphs

The main way for defining equivalence among acyclic directed graphs is b...

0 AmirEmad Ghassami, et al. ∙

∙ 10/12/2019

Interventional Experiment Design for Causal Structure Learning

It is known that from purely observational data, a causal DAG is identif...

0 AmirEmad Ghassami, et al. ∙

∙ 08/11/2019

Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables

We consider the problem of learning causal models from observational dat...

0 Saber Salehkaleybar, et al. ∙

∙ 06/04/2018

REORDER: Securing Dynamic-Priority Real-Time Systems Using Schedule Obfuscation

Modern real-time systems (RTS) are increasingly the focus of security th...

0 Chien-Ying Chen, et al. ∙

∙ 02/05/2018

Counting and Uniform Sampling from Markov Equivalent DAGs

We propose an exact solution for the problem of finding the size of a Ma...

0 AmirEmad Ghassami, et al. ∙

∙ 01/13/2018

Fairness in Supervised Learning: An Information Theoretic Approach

Automated decision making systems are increasingly being used in real-wo...

0 AmirEmad Ghassami, et al. ∙

∙ 09/11/2017

Budgeted Experiment Design for Causal Structure Learning

We study the problem of causal structure learning when the experimenter ...

0 AmirEmad Ghassami, et al. ∙

∙ 05/26/2017

Learning Causal Structures Using Regression Invariance

We study causal inference in a multi-environment setting, in which the f...

0 AmirEmad Ghassami, et al. ∙

∙ 05/07/2017

A Reconnaissance Attack Mechanism for Fixed-Priority Real-Time Systems

In real-time embedded systems (RTS), failures due to security breaches c...

0 Chien-Ying Chen, et al. ∙

∙ 02/27/2017

Optimal Experiment Design for Causal Discovery from Fixed Number of Experiments

We study the problem of causal structure learning over a set of random v...

0 AmirEmad Ghassami, et al. ∙

∙ 01/30/2017

Interaction Information for Causal Inference: The Case of Directed Triangle

Interaction information is one of the multivariate generalizations of mu...

0 AmirEmad Ghassami, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world