Survival models capture the relationship between an accumulating hazard ...
Derivative-based algorithms are ubiquitous in statistics, machine learni...
This short note reviews the basic theory for quantifying both the asympt...
A complete recipe of measure-preserving diffusions in Euclidean space wa...
Inferences about hypotheses are ubiquitous in the cognitive sciences. Ba...
Gradient-based techniques are becoming increasingly critical in quantita...
Accelerated gradient methods are a powerful optimization tool in machine...
Experiments in research on memory, language, and in other areas of cogni...
First-order automatic differentiation is a ubiquitous tool across statis...
Sociologically-inclined literary history foundered in the 20th century d...
Verifying the correctness of Bayesian computation is challenging. This i...
As the frontiers of applied statistics progress through increasingly com...
Accelerated gradient methods have had significant impact in machine lear...
We establish general conditions under which Markov chains produced by th...
As computational challenges in optimization and statistical inference gr...