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Calibrated Elastic Regularization in Matrix Completion
Tingni Sun, Cun-Hui Zhang
This paper concerns the problem of matrix completion, which is to estimate a matrix from observations in a small subset of indices. We propose a calibrated spectrum elastic net met…
Correlated variables in regression: clustering and sparse estimation
Peter Bühlmann, Philipp Rütimann, Sara van de Geer +1
We consider estimation in a high-dimensional linear model with strongly correlated variables. We propose to cluster the variables first and do subsequent sparse estimation such as…
One Permutation Hashing for Efficient Search and Learning
Ping Li, Art Owen, Cun-Hui Zhang
Recently, the method of b-bit minwise hashing has been applied to large-scale linear learning and sublinear time near-neighbor search. The major drawback of minwise hashing is the…
Sparse Matrix Inversion with Scaled Lasso
Tingni Sun, Cun-Hui Zhang
We propose a new method of learning a sparse nonnegative-definite target matrix. Our primary example of the target matrix is the inverse of a population covariance or correlation m…
A General Framework of Dual Certificate Analysis for Structured Sparse Recovery Problems
Cun-Hui Zhang, Tong Zhang
This paper develops a general theoretical framework to analyze structured sparse recovery problems using the notation of dual certificate. Although certain aspects of the dual cert…