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AAAI
2007
15 years 8 months ago
Learning Large Scale Common Sense Models of Everyday Life
Recent work has shown promise in using large, publicly available, hand-contributed commonsense databases as joint models that can be used to infer human state from day-to-day sens...
William Pentney, Matthai Philipose, Jeff A. Bilmes...
CGF
2008
153views more  CGF 2008»
15 years 6 months ago
Computing Local Signed Distance Fields for Large Polygonal Models
The signed distance field for a polygonal model is a useful representation that facilitates efficient computation in many visualization and geometric processing tasks. Often it is...
Byungjoon Chang, Deukhyun Cha, Insung Ihm
CORR
2010
Springer
130views Education» more  CORR 2010»
15 years 6 months ago
Approximated Structured Prediction for Learning Large Scale Graphical Models
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
Tamir Hazan, Raquel Urtasun
CMG
2003
15 years 7 months ago
{Performance Modeling and Evaluation of Large-Scale J2EE Applications
The queueing Petri net (QPN) paradigm provides a number of benefits over conventional modeling paradigms such as queueing networks and generalized stochastic Petri nets. Using qu...
Samuel Kounev, Alejandro P. Buchmann
ICCV
2007
IEEE
16 years 8 months ago
Non-Linear Beam Model for Tracking Large Deformations
In this paper we investigate physics-based plane beam model, frequently used in mechanical and civil engineering, to track large non-linear deformations in images. Such models do ...
Slobodan Ilic, Pascal Fua