K. Wang

activity

20192025

most citedSimplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints

19 citations · 21 across the 4 of their papers we have counts for

collaborators

Showing 2019Show all

2 papers · 1 filter

cs.LG2019

$D C^{2}$ : A Divide-and-conquer Algorithm for Large-scale Kernel Learning with Application to Clustering

Ke Alexander Wang, Xinran Bian, Pan Liu +1

Divide-and-conquer is a general strategy to deal with large scale problems. It is typically applied to generate ensemble instances, which potentially limits the problem size it can…

cs.LG2019

Exact Gaussian Processes on a Million Data Points

Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner +3

Gaussian processes (GPs) are flexible non-parametric models, with a capacity that grows with the available data. However, computational constraints with standard inference procedur…

DC2: A Divide-and-conquer Algorithm for Large-scale Kernel Learning with Application to Clustering

Exact Gaussian Processes on a Million Data Points

$D C^{2}$ : A Divide-and-conquer Algorithm for Large-scale Kernel Learning with Application to Clustering