Sciweavers

733 search results - page 71 / 147
» Learning Riemannian Metrics
Sort
View
TIT
1998
70views more  TIT 1998»
15 years 6 months ago
The Importance of Convexity in Learning with Squared Loss
We show that if the closureof a function class F under the metric induced by some probability distribution is not convex, then the sample complexity for agnostically learning F wi...
Wee Sun Lee, Peter L. Bartlett, Robert C. Williams...
ICPR
2006
IEEE
16 years 7 months ago
A New Data Selection Principle for Semi-Supervised Incremental Learning
Current semi-supervised incremental learning approaches select unlabeled examples with predicted high confidence for model re-training. We show that for many applications this dat...
Alexander I. Rudnicky, Rong Zhang
IROS
2008
IEEE
135views Robotics» more  IROS 2008»
16 years 22 days ago
Interactive learning of visual topological navigation
— We present a topological navigation system that is able to visually recognize the different rooms of an apartment and guide a robot between them. Specifically tailored for sma...
David Filliat
ECAI
2004
Springer
15 years 11 months ago
Avatars That Learn How to Behave
It is possible to model avatars that learn to simulate object manipulations and other complex actions. A number of applications may benefit from this technique including safety, e...
Adam Szarowicz, Paolo Remagnino
BIS
2008
132views Business» more  BIS 2008»
15 years 7 months ago
Evaluate - An Innovative Service for Learning Performance Monitoring in Businesses
In this paper we present Evaluate, a platform for learning performance monitoring. Evaluate manages a number of artefacts that can be used to monitor learning performance, like met...
Bernd Simon, Kasra Seirafi, Asmund Realfsen, Mark ...