We describe a simple deterministic near-linear time approximation scheme...
Given a set of points P = (P^+ ⊔ P^-) ⊂ℝ^d for some
constant d and a sup...
We develop a new model of insulin-glucose dynamics for forecasting blood...
One of the challenges in machine learning research is to ensure that
pre...
Deep generative models have recently yielded encouraging results in prod...
While most classical approaches to Granger causality detection assume li...
Providing long-range forecasts is a fundamental challenge in time series...
A determinantal point process (DPP) is a probabilistic model of set dive...
Although there is a rich literature on methods for allowing the variance...