6 citations · 13 across the 6 of their papers we have counts for
13 papers
Learning Circular Hidden Quantum Markov Models: A Tensor Network Approach
Mohammad Ali Javidian, Vaneet Aggarwal, Zubin Jacob
In this paper, we propose circular Hidden Quantum Markov Models (c-HQMMs), which can be applied for modeling temporal data in quantum datasets (with classical datasets as a special…
Accelerating Recursive Partition-Based Causal Structure Learning
Md. Musfiqur Rahman, Ayman Rasheed, Md. Mosaddek Khan +3
Causal structure discovery from observational data is fundamental to the causal understanding of autonomous systems such as medical decision support systems, advertising campaigns…
CADET: Debugging and Fixing Misconfigurations using Counterfactual Reasoning
Rahul Krishna, Md Shahriar Iqbal, Mohammad Ali Javidian +2
Modern computing platforms are highly-configurable with thousands of interacting configurations. However, configuring these systems is challenging. Erroneous configurations can cau…
Learning LWF Chain Graphs: A Markov Blanket Discovery Approach
Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi
This paper provides a graphical characterization of Markov blankets in chain graphs (CGs) under the Lauritzen-Wermuth-Frydenberg (LWF) interpretation. The characterization is diffe…
Learning LWF Chain Graphs: an Order Independent Algorithm
Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi
LWF chain graphs combine directed acyclic graphs and undirected graphs. We present a PC-like algorithm that finds the structure of chain graphs under the faithfulness assumption to…
AMP Chain Graphs: Minimal Separators and Structure Learning Algorithms
Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi
We address the problem of finding a minimal separator in an Andersson-Madigan-Perlman chain graph (AMP CG), namely, finding a set Z of nodes that separates a given nonadjacent pair…