307 citations · 693 across the 70 of their papers we have counts for
4 papers · 1 filter
Modeling item--item similarities for personalized recommendations on Yahoo! front page
Deepak Agarwal, Liang Zhang, Rahul Mazumder
We consider the problem of algorithmically recommending items to users on a Yahoo! front page module. Our approach is based on a novel multilevel hierarchical model that we refer t…
The Graphical Lasso: New Insights and Alternatives
Rahul Mazumder, Trevor Hastie
The graphical lasso \citep{FHT2007a} is an algorithm for learning the structure in an undirected Gaussian graphical model, using regularization to control the number of ze…
A Flexible, Scalable and Efficient Algorithmic Framework for Primal Graphical Lasso
Rahul Mazumder, Deepak K. Agarwal
We propose a scalable, efficient and statistically motivated computational framework for Graphical Lasso (Friedman et al., 2007b) - a covariance regularization framework that has r…
Exact covariance thresholding into connected components for large-scale Graphical Lasso
Rahul Mazumder, Trevor Hastie
We consider the sparse inverse covariance regularization problem or graphical lasso with regularization parameter . Suppose the co- variance graph formed by thresholding the ent…