29 citations · 65 across the 13 of their papers we have counts for
13 papers · 1 filter
Consistent Interpolating Ensembles via the Manifold-Hilbert Kernel
Yutong Wang, Clayton D. Scott
Recent research in the theory of overparametrized learning has sought to establish generalization guarantees in the interpolating regime. Such results have been established for a f…
VC dimension of partially quantized neural networks in the overparametrized regime
Yutong Wang, Clayton D. Scott
Vapnik-Chervonenkis (VC) theory has so far been unable to explain the small generalization error of overparametrized neural networks. Indeed, existing applications of VC theory to…
An Exact Solver for the Weston-Watkins SVM Subproblem
Yutong Wang, Clayton D. Scott
Recent empirical evidence suggests that the Weston-Watkins support vector machine is among the best performing multiclass extensions of the binary SVM. Current state-of-the-art sol…
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations
Alexander Ritchie, Robert A. Vandermeulen, Clayton Scott
Recent research has established sufficient conditions for finite mixture models to be identifiable from grouped observations. These conditions allow the mixture components to be no…
Weston-Watkins Hinge Loss and Ordered Partitions
Yutong Wang, Clayton D. Scott
Multiclass extensions of the support vector machine (SVM) have been formulated in a variety of ways. A recent empirical comparison of nine such formulations [Doǧan et al. 2016] rec…
Learning from Multiple Corrupted Sources, with Application to Learning from Label Proportions
Clayton Scott, Jianxin Zhang
We study binary classification in the setting where the learner is presented with multiple corrupted training samples, with possibly different sample sizes and degrees of corruptio…