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» Scales and Scale-like Structures
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CVPR
2006
IEEE
16 years 1 months ago
Depth from Familiar Objects: A Hierarchical Model for 3D Scenes
We develop an integrated, probabilistic model for the appearance and three-dimensional geometry of cluttered scenes. Object categories are modeled via distributions over the 3D lo...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
ICTAI
2006
IEEE
16 years 1 months ago
Learning to Predict Salient Regions from Disjoint and Skewed Training Sets
We present an ensemble learning approach that achieves accurate predictions from arbitrarily partitioned data. The partitions come from the distributed processing requirements of ...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
AUSAI
2005
Springer
16 years 18 days ago
Global Versus Local Constructive Function Approximation for On-Line Reinforcement Learning
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
Peter Vamplew, Robert Ollington
ISSAC
2005
Springer
115views Mathematics» more  ISSAC 2005»
16 years 17 days ago
Algorithms for the non-monic case of the sparse modular GCD algorithm
Let G = (4y2 + 2z)x2 + (10y2 + 6z) be the greatest common divisor (gcd) of two polynomials A, B ∈   [x,y, z]. Because G is not monic in the main variable x, the sparse modular ...
Jennifer de Kleine, Michael B. Monagan, Allan D. W...
MSWIM
2003
ACM
16 years 9 days ago
Simulation of large ad hoc networks
An ad hoc network is formed by wireless mobile nodes (hosts) that operate as terminals as well as routers in the network, without any centralized administration. Research in ad ho...
Valeriy Naoumov, Thomas R. Gross