
Quantum Causal Inference in the Presence of Hidden Common Causes: an Entropic Approach
Quantum causality is an emerging field of study which has the potential ...
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Scalable Causal Transfer Learning
One of the most important problems in transfer learning is the task of d...
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Quantum Entropic Causal Inference
As quantum computing and networking nodes scaleup, important open quest...
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Accelerating Recursive PartitionBased Causal Structure Learning
Causal structure discovery from observational data is fundamental to the...
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CADET: A Systematic Method For Debugging Misconfigurations using Counterfactual Reasoning
Modern computing platforms are highlyconfigurable with thousands of int...
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Learning LWF Chain Graphs: A Markov Blanket Discovery Approach
This paper provides a graphical characterization of Markov blankets in c...
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Learning LWF Chain Graphs: an Order Independent Algorithm
LWF chain graphs combine directed acyclic graphs and undirected graphs. ...
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AMP Chain Graphs: Minimal Separators and Structure Learning Algorithms
We address the problem of finding a minimal separator in an AnderssonMa...
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OrderIndependent Structure Learning of Multivariate Regression Chain Graphs
This paper deals with multivariate regression chain graphs (MVR CGs), wh...
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Transfer Learning for Performance Modeling of Configurable Systems: A Causal Analysis
Modern systems (e.g., deep neural networks, big data analytics, and comp...
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On a hypergraph probabilistic graphical model
We propose a directed acyclic hypergraph framework for a probabilistic g...
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Comment on: Decomposition of structural learning about directed acyclic graphs [1]
We propose an alternative proof concerning necessary and sufficient cond...
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A Proof of the FrontDoor Adjustment Formula
We provide a proof of the the FrontDoor adjustment formula using the do...
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Structural Learning of Multivariate Regression Chain Graphs via Decomposition
We extend the decomposition approach for learning Bayesian networks (BN)...
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On the Properties of MVR Chain Graphs
Depending on the interpretation of the type of edges, a chain graph can ...
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The evolution of multivariate regression chain graphs
Depending on the interpretation of the type of edges, a chain graph can ...
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The evolution of the global Markov property for multivariate regression graphs: differences and conflicts
Depending on the interpretation of the type of edges, a chain graph can ...
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How can social planners prevent disappointment in an election?
Mechanism design is concerned with settings where a policy maker (or soc...
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Mohammad ali Javidian
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