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FOCS
1994
IEEE
15 years 10 months ago
The Power of Team Exploration: Two Robots Can Learn Unlabeled Directed Graphs
We show that two cooperating robots can learn exactly any strongly-connected directed graph with n indistinguishable nodes in expected time polynomial in n. We introduce a new typ...
Michael A. Bender, Donna K. Slonim
AROBOTS
2005
114views more  AROBOTS 2005»
15 years 6 months ago
Visually Guided Cooperative Robot Actions Based on Information Quality
In field environments it is not usually possible to provide robots in advance with valid geometric models of its environment and task element locations. The robot or robot teams ne...
Vivek A. Sujan, Steven Dubowsky
CVPR
2005
IEEE
16 years 8 months ago
Online Learning of Probabilistic Appearance Manifolds for Video-Based Recognition and Tracking
This paper presents an online learning algorithm to construct from video sequences an image-based representation that is useful for recognition and tracking. For a class of object...
Kuang-Chih Lee, David J. Kriegman
ECCV
2002
Springer
16 years 8 months ago
Audio-Video Sensor Fusion with Probabilistic Graphical Models
Abstract. We present a new approach to modeling and processing multimedia data. This approach is based on graphical models that combine audio and video variables. We demonstrate it...
Matthew J. Beal, Hagai Attias, Nebojsa Jojic
ICML
2006
IEEE
16 years 7 months ago
Probabilistic inference for solving discrete and continuous state Markov Decision Processes
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
Marc Toussaint, Amos J. Storkey