Meixia LIN

MACE: Mixture-Of-Experts Accelerated Coordinate Encoding for Large-Scale Scene Localization and Rendering

DNNLasso: Scalable Graph Learning for Matrix-Variate Data

We consider the problem of jointly learning row-wise and column-wise dependencies of matrix-variate observations, which are modelled separately by two precision matrices. Due to the complicated structure of Kronecker-product precision matrices in the commonly used matrix-variate Gaussian graphical m…

Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD

Stochastic gradient descent (SGD) is a cornerstone of machine learning. When the number $N$ of data items is large, SGD relies on constructing an unbiased estimator of the gradient of the empirical risk using a small subset of the original dataset, called a minibatch. Default minibatch construction…