Logarithms of determinants of large positive definite matrices appear ubiquitously in machine learning applications including Gaussian graphical and Gaussian process models, partition functions ofâ€¦ (More)

Computation of the trace of a matrix function plays an important role in many scientific computing applications, including applications in machine learning, computational physics (e.g., latticeâ€¦ (More)

Computation of the trace of a matrix function plays an important role in many scientific computing applications, including applications in machine learning, computational physics (e.g., latticeâ€¦ (More)

Determinantal point processes (DPPs) are popular probabilistic models that arise in many machine learning tasks, where distributions of diverse sets are characterized by matrix determinants. In thisâ€¦ (More)

The trace of matrix functions, often called spectral sums, e.g., rank, log-determinant and nuclear norm, appear in many machine learning tasks. However, optimizing or computing such (parameterized)â€¦ (More)

A large class of machine learning techniques requires the solution of optimization problems involving spectral functions of parametric matrices, e.g. log-determinant and nuclear norm. Unfortunately,â€¦ (More)