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» Sampling-Based Motion Planning Using Predictive Models
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CVPR
2007
IEEE
15 years 23 days ago
Discriminative Learning of Dynamical Systems for Motion Tracking
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
Minyoung Kim, Vladimir Pavlovic
SMA
1999
ACM
107views Solid Modeling» more  SMA 1999»
14 years 3 months ago
Generation of swept volumes of toroidal endmills in five-axis motion using space curves
Accurate prediction of the swept volume of a cutting tool is essential in NC verification algorithms for detecting deficiencies in a proposed tool path, such as gouging, undercutt...
David Roth, Sanjeev Bedi, Fathy Ismail
IM
2007
14 years 5 days ago
Estimating End-to-End Performance by Collaborative Prediction with Active Sampling
— Accurately estimating end-to-end performance in distributed systems is essential both for monitoring compliance with service-level agreements (SLAs) and for performance optimiz...
Irina Rish, Gerald Tesauro
ICML
2009
IEEE
14 years 11 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
AMI
2010
Springer
13 years 8 months ago
Taxi-Aware Map: Identifying and Predicting Vacant Taxis in the City
Knowing where vacant taxis are and will be at a given time and location helps the users in daily planning and scheduling, as well as the taxi service providers in dispatching. In t...
Santi Phithakkitnukoon, Marco Veloso, Carlos Bento...