A new technical paper titled “Computing high-degree polynomial gradients in memory” was published by researchers at UCSB, HP Labs, Forschungszentrum Juelich GmbH, and RWTH Aachen University.
In this course, you’ll learn theoretical foundations of optimization methods used for training deep machine learning models. Why does gradient descent work? Specifically, what can we guarantee about ...
This paper proposes a path-based algorithm for solving the well-known logit-based stochastic user equilibrium (SUE) problem in transportation planning and management. Based on the gradient projection ...
We develop and evaluate a large-scale dynamic vegetation model, TEM-LPJ, which considers interactions among water, light and nitrogen in simulating ecosystem function and structure. We parameterized ...