9 citations · 9 across the 1 of their papers we have counts for
4 papers
Reducing Sampling Ratios Improves Bagging in Sparse Regression
Luoluo Liu, Sang Peter Chin, Trac D. Tran
Bagging, a powerful ensemble method from machine learning, improves the performance of unstable predictors. Although the power of Bagging has been shown mostly in classification pr…
JOBS: Joint-Sparse Optimization from Bootstrap Samples
Luoluo Liu, Sang Peter Chin, Trac D. Tran
Classical signal recovery based on minimization solves the least squares problem with all available measurements via sparsity-promoting regularization. In practice, it is…
Sparse Coding and Autoencoders
Akshay Rangamani, Anirbit Mukherjee, Amitabh Basu +4
In "Dictionary Learning" one tries to recover incoherent matrices (typically overcomplete and whose columns are assumed to be normalized) and spar…
Automatic Vertebra Labeling in Large-Scale 3D CT using Deep Image-to-Image Network with Message Passing and Sparsity Regularization
Dong Yang, Tao Xiong, Daguang Xu +10
Automatic localization and labeling of vertebra in 3D medical images plays an important role in many clinical tasks, including pathological diagnosis, surgical planning and postope…