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11/25/2022
High-Dimensional Causal Discovery: Learning from Inverse Covariance via Independence-based Decomposition
Inferring causal relationships from observational data is a fundamental ...
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04/10/2022
From graphs to DAGs: a low-complexity model and a scalable algorithm
Learning directed acyclic graphs (DAGs) is long known a critical challen...
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03/13/2022
On the analysis of optimization with fixed-rank matrices: a quotient geometric view
We study a type of Riemannian gradient descent (RGD) algorithm, designed...
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01/26/2021
New Riemannian preconditioned algorithms for tensor completion via polyadic decomposition
We propose new Riemannian preconditioned algorithms for low-rank tensor ...
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08/28/2020