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NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion
Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh +2
We develop an efficient parallel distributed algorithm for matrix completion, named NOMAD (Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix…
A Divide-and-Conquer Solver for Kernel Support Vector Machines
Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
The kernel support vector machine (SVM) is one of the most widely used classification methods; however, the amount of computation required becomes the bottleneck when facing millio…
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation
Cho-Jui Hsieh, Matyas A. Sustik, Inderjit S. Dhillon +1
The L1-regularized Gaussian maximum likelihood estimator (MLE) has been shown to have strong statistical guarantees in recovering a sparse inverse covariance matrix, or alternative…
Prediction and Clustering in Signed Networks: A Local to Global Perspective
Kai-Yang Chiang, Cho-Jui Hsieh, Nagarajan Natarajan +2
The study of social networks is a burgeoning research area. However, most existing work deals with networks that simply encode whether relationships exist or not. In contrast, rela…