3 citations · 4 across the 5 of their papers we have counts for
5 papers
Multi-Robot Multitask Gaussian Process Estimation and Coverage
Lai Wei, Andrew McDonald, Vaibhav Srivastava
Coverage control is essential for the optimal deployment of agents to monitor or cover areas with sensory demands. While traditional coverage involves single-task robots, increasin…
Learning with Optimal Interpolation Norms
Patrick L. Combettes, Andrew M. McDonald, Charles A. Micchelli +1
We analyze a class of norms defined via an optimal interpolation problem involving the composition of norms and a linear operator. This construction, known as infimal postcompositi…
Fitting Spectral Decay with the -Support Norm
Andrew M. McDonald, Massimiliano Pontil, Dimitris Stamos
The spectral -support norm enjoys good estimation properties in low rank matrix learning problems, empirically outperforming the trace norm. Its unit ball is the convex hull of…
New Perspectives on -Support and Cluster Norms
Andrew M. McDonald, Massimiliano Pontil, Dimitris Stamos
We study a regularizer which is defined as a parameterized infimum of quadratics, and which we call the box-norm. We show that the k-support norm, a regularizer proposed by [Argyri…
New Perspectives on k-Support and Cluster Norms
Andrew M. McDonald, Massimiliano Pontil, Dimitris Stamos
The -support norm is a regularizer which has been successfully applied to sparse vector prediction problems. We show that it belongs to a general class of norms which can be for…