Treatment Effect Estimation Under Additive Hazards Models With High-Dimension…

Estimating treatment effects for survival outcomes in the high-dimensional setting is critical for many biomedical applications and any application with censored observations. This article establis…

Potential Function-Based Framework for Minimizing Gradients in Convex and Min…

Making the gradients small is a fundamental optimization problem that has eluded unifying and simple convergence arguments in first-order optimization, so far primarily reserved for other convergen…

Fixed Effects Testing in High-Dimensional Linear Mixed Models

Rejoinder to "A Tuning-Free Robust and Efficient Approach to High-Dimensional…

A Tuning-Free Robust and Efficient Approach to High-Dimensional Regression

Generalized Momentum-Based Methods : A Hamiltonian Perspective

We take a Hamiltonian-based perspective to generalize Nesterov's accelerated gradient descent and Polyak's heavy ball method to a broad class of momentum methods in the setting of (possibly) constr…

Fair Packing and Covering on a Relative Scale

Optical Nonlinearity Monitoring and Launch Power Optimization by Artificial N…

CMOS-Compatible Optical Phased Array Powered by a Monolithically-Integrated E…

Automated Fiber Type Identification in SDN-Enabled Optical Networks