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09/02/2022
Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion
Knowledge graphs (KGs) are known for their large scale and knowledge inf...
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01/12/2021
A unified framework for correlation mining in ultra-high dimension
An important problem in large scale inference is the identification of v...
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05/11/2015
Foundational principles for large scale inference: Illustrations through correlation mining
When can reliable inference be drawn in the "Big Data" context? This pap...
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02/22/2015
Two-stage Sampling, Prediction and Adaptive Regression via Correlation Screening (SPARCS)
This paper proposes a general adaptive procedure for budget-limited pred...
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05/13/2014
G-AMA: Sparse Gaussian graphical model estimation via alternating minimization
Several methods have been recently proposed for estimating sparse Gaussi...
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10/09/2013
Duality in Graphical Models
Graphical models have proven to be powerful tools for representing high-...
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07/20/2013
A convex pseudo-likelihood framework for high dimensional partial correlation estimation with convergence guarantees
Sparse high dimensional graphical model selection is a topic of much int...
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03/10/2013
Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension
We introduce a new approach to variable selection, called Predictive Cor...
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11/12/2012
Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation
The L1-regularized maximum likelihood estimation problem has recently be...
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11/11/2011
A note on the lack of symmetry in the graphical lasso
The graphical lasso (glasso) is a widely-used fast algorithm for estimat...
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02/06/2011
