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» Approximate Learning of Dynamic Models
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ICML
2008
IEEE
16 years 5 months ago
Graph kernels between point clouds
Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and pra...
Francis R. Bach
ICML
2010
IEEE
15 years 6 months ago
Probabilistic Backward and Forward Reasoning in Stochastic Relational Worlds
Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...
Tobias Lang, Marc Toussaint
154
Voted
EWSN
2004
Springer
16 years 4 months ago
Context-Aware Sensors
Wireless sensor networks typically consist of a large number of sensor nodes embedded in a physical space. Such sensors are low-power devices that are primarily used for monitoring...
Eiman Elnahrawy, Badri Nath
CVPR
2007
IEEE
16 years 7 months ago
Beyond bottom-up: Incorporating task-dependent influences into a computational model of spatial attention
A critical function in both machine vision and biological vision systems is attentional selection of scene regions worthy of further analysis by higher-level processes such as obj...
Robert J. Peters, Laurent Itti
137
Voted
ATAL
2006
Springer
15 years 8 months ago
Efficient agent-based models for non-genomic evolution
Modeling dynamical systems composed of aggregations of primitive proteins is critical to the field of astrobiological science, which studies early evolutionary structures dealing ...
Nachi Gupta, Adrian K. Agogino, Kagan Tumer