50 citations · 383 across the 69 of their papers we have counts for
7 papers · 1 filter
Learning Bayesian Networks in the Presence of Structural Side Information
Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi +2
We study the problem of learning a Bayesian network (BN) of a set of variables when structural side information about the system is available. It is well known that learning the st…
Causal Discovery in Linear Structural Causal Models with Deterministic Relations
Yuqin Yang, Mohamed Nafea, AmirEmad Ghassami +1
Linear structural causal models (SCMs) -- in which each observed variable is generated by a subset of the other observed variables as well as a subset of the exogenous sources -- a…
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias
Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami +1
We consider the problem of learning the causal MAG of a system from observational data in the presence of latent variables and selection bias. Constraint-based methods are one of t…
Causal Effect Identification with Context-specific Independence Relations of Control Variables
Ehsan Mokhtarian, Fateme Jamshidi, Jalal Etesami +1
We study the problem of causal effect identification from observational distribution given the causal graph and some context-specific independence (CSI) relations. It was recently…
Information Theoretic Measures for Fairness-aware Feature Selection
Sajad Khodadadian, Mohamed Nafea, AmirEmad Ghassami +1
Machine learning algorithms are increasingly used for consequential decision making regarding individuals based on their relevant features. Features that are relevant for accurate…
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization
Siqi Zhang, Junchi Yang, Cristóbal Guzmán +2
This paper studies the complexity for finding approximate stationary points of nonconvex-strongly-concave (NC-SC) smooth minimax problems, in both general and averaged smooth finit…
Impact of Data Processing on Fairness in Supervised Learning
Sajad Khodadadian, AmirEmad Ghassami, Negar Kiyavash
We study the impact of pre and post processing for reducing discrimination in data-driven decision makers. We first analyze the fundamental trade-off between fairness and accuracy…