33 citations · 36 across the 4 of their papers we have counts for
4 papers
Scalable and Differentiable Point-Cloud Registration Using Maximum Mean Discrepancy
Rixon Crane, Fahira Afzal Maken, Nicholas Lawrance +4
We present MMD-Reg, a novel correspondence-free approach to point-cloud registration that is differentiable and has linear computational complexity in the number of points. We mode…
Invexifying Regularization of Non-Linear Least-Squares Problems
Rixon Crane, Fred Roosta
We consider regularization of non-convex optimization problems involving a non-linear least-squares objective. By adding an auxiliary set of variables, we introduce a novel regular…
DINO: Distributed Newton-Type Optimization Method
Rixon Crane, Fred Roosta
We present a novel communication-efficient Newton-type algorithm for finite-sum optimization over a distributed computing environment. Our method, named DINO, overcomes both theore…
DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization
Rixon Crane, Fred Roosta
For optimization of a sum of functions in a distributed computing environment, we present a novel communication efficient Newton-type algorithm that enjoys a variety of advantages…