The notion of algorithmic stability has been used effectively in the past to derive tight generalization bounds. A key advantage of these bounds is that they are designed for spec...
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
This paper investigates “Schelling points” on 3D meshes, feature points selected by people in a pure coordination game due to their salience. To collect data for this investig...
Xiaobai Chen, Abulhair Saparov, Bill Pang, Thomas ...
Markov decisionprocesses(MDPs) haveproven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, stat...
Current work in object categorization discriminates
among objects that typically possess gross differences
which are readily apparent. However, many applications
require making ...
Andrew Moldenke, Asako Yamamuro, David A. Lytle, E...