
Information Theoretic Measures for Fairnessaware Feature Selection
Machine learning algorithms are increasingly used for consequential deci...
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Multiply Robust Causal Mediation Analysis with Continuous Treatments
In many applications, researchers are interested in the direct and indir...
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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...
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Impact of Data Processing on Fairness in Supervised Learning
We study the impact of pre and post processing for reducing discriminati...
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A Recursive Markov BlanketBased Approach to Causal Structure Learning
One of the main approaches for causal structure learning is constraintb...
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On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
Learning graphical structure based on Directed Acyclic Graphs (DAGs) is ...
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ModelAugmented NearestNeighbor Estimation of Conditional Mutual Information for Feature Selection
Markov blanket feature selection, while theoretically optimal, generally...
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Characterizing Distribution Equivalence for Cyclic and Acyclic Directed Graphs
The main way for defining equivalence among acyclic directed graphs is b...
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Interventional Experiment Design for Causal Structure Learning
It is known that from purely observational data, a causal DAG is identif...
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Learning Linear NonGaussian Causal Models in the Presence of Latent Variables
We consider the problem of learning causal models from observational dat...
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REORDER: Securing DynamicPriority RealTime Systems Using Schedule Obfuscation
Modern realtime systems (RTS) are increasingly the focus of security th...
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Counting and Uniform Sampling from Markov Equivalent DAGs
We propose an exact solution for the problem of finding the size of a Ma...
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Fairness in Supervised Learning: An Information Theoretic Approach
Automated decision making systems are increasingly being used in realwo...
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Budgeted Experiment Design for Causal Structure Learning
We study the problem of causal structure learning when the experimenter ...
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Learning Causal Structures Using Regression Invariance
We study causal inference in a multienvironment setting, in which the f...
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A Reconnaissance Attack Mechanism for FixedPriority RealTime Systems
In realtime embedded systems (RTS), failures due to security breaches c...
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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...
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Interaction Information for Causal Inference: The Case of Directed Triangle
Interaction information is one of the multivariate generalizations of mu...
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AmirEmad Ghassami
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