Linear algebra is a work-horse of numerical computing. Tensor algebra is a generalization of linear algebra with applications in scientific computing, machine learning, and data analytics. Tensors are often sparse and compound operations must frequently…
Noisy data, non-convex objectives, model misspecification, and numerical instability can all cause undesired behaviors in machine learning systems. As a result, detecting actual implementation errors can be extremely difficult. We demonstrate a methodology in which…
In Bayesian analysis, the posterior follows from the data and a choice of a prior and a likelihood. These choices may be somewhat subjective and reasonably vary over some range. Thus, we wish to measure…
