Sciweavers

260 search results - page 6 / 52
» Automatic selection of task spaces for imitation learning
Sort
View
ICRA
2009
IEEE
179views Robotics» more  ICRA 2009»
14 years 1 months ago
Automatic weight learning for multiple data sources when learning from demonstration
— Traditional approaches to programming robots are generally inaccessible to non-robotics-experts. A promising exception is the Learning from Demonstration paradigm. Here a polic...
Brenna Argall, Brett Browning, Manuela M. Veloso
CVPR
2009
IEEE
15 years 1 months ago
Learning to Track with Multiple Observers
We propose a novel approach to designing algorithms for object tracking based on fusing multiple observation models. As the space of possible observation models is too large for...
Björn Stenger, Roberto Cipolla, Thomas Woodle...
IUI
2010
ACM
14 years 1 months ago
Automatically identifying targets users interact with during real world tasks
Information about the location and size of the targets that users interact with in real world settings can enable new innovations in human performance assessment and software usab...
Amy Hurst, Scott E. Hudson, Jennifer Mankoff
NIPS
1994
13 years 8 months ago
Phase-Space Learning
In this paper, we present an improved version of the online phase-space learning algorithm of Tsung and Cottrell (1995), called ARTISTE (Autonomous Real-TIme Selection of Training...
Fu-Sheng Tsung, Garrison W. Cottrell
CEC
2008
IEEE
14 years 1 months ago
Learning what to ignore: Memetic climbing in topology and weight space
— We present the memetic climber, a simple search algorithm that learns topology and weights of neural networks on different time scales. When applied to the problem of learning ...
Julian Togelius, Faustino J. Gomez, Jürgen Sc...