240 citations · 441 across the 6 of their papers we have counts for
8 papers
Fully Homomorphic Encryption for Statistical Modeling
Balasubramanian Narasimhan
Fully homomorphic encryption allows arithmetic to be carried out on encrypted values, so that a party performing a computation need not see the data it operates on. This is useful…
Cooperative learning for multiview analysis
Daisy Yi Ding, Shuangning Li, Balasubramanian Narasimhan +1
We propose a new method for supervised learning with multiple sets of features ("views"). The multiview problem is especially important in biology and medicine, where "-omics" data…
Elastic Net Regularization Paths for All Generalized Linear Models
J. Kenneth Tay, Balasubramanian Narasimhan, Trevor Hastie
The lasso and elastic net are popular regularized regression models for supervised learning. Friedman, Hastie, and Tibshirani (2010) introduced a computationally efficient algorith…
A Scalable Discrete-Time Survival Model for Neural Networks
Michael F. Gensheimer, Balasubramanian Narasimhan
There is currently great interest in applying neural networks to prediction tasks in medicine. It is important for predictive models to be able to use survival data, where each pat…
Imputation of mixed data with multilevel singular value decomposition
François Husson, Julie Josse, Balasubramanian Narasimhan +1
Statistical analysis of large data sets offers new opportunities to better understand many processes. Yet, data accumulation often implies relaxing acquisition procedures or compou…
CVXR: An R Package for Disciplined Convex Optimization
Anqi Fu, Balasubramanian Narasimhan, Stephen Boyd
CVXR is an R package that provides an object-oriented modeling language for convex optimization, similar to CVX, CVXPY, YALMIP, and Convex.jl. It allows the user to formulate conve…