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FLAIRS
2009
13 years 6 months ago
Mapping Grounded Object Properties across Perceptually Heterogeneous Embodiments
As robots become more common, it becomes increasingly useful for them to communicate and effectively share knowledge that they have learned through their individual experiences. L...
Zsolt Kira
TIT
1998
70views more  TIT 1998»
13 years 8 months ago
The Importance of Convexity in Learning with Squared Loss
We show that if the closureof a function class F under the metric induced by some probability distribution is not convex, then the sample complexity for agnostically learning F wi...
Wee Sun Lee, Peter L. Bartlett, Robert C. Williams...
ICML
1996
IEEE
14 years 9 months ago
Discretizing Continuous Attributes While Learning Bayesian Networks
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
Moisés Goldszmidt, Nir Friedman
NECO
2010
97views more  NECO 2010»
13 years 7 months ago
Rademacher Chaos Complexities for Learning the Kernel Problem
In this paper we develop a novel generalization bound for learning the kernel problem. First, we show that the generalization analysis of the kernel learning problem reduces to in...
Yiming Ying, Colin Campbell
PAMI
1998
113views more  PAMI 1998»
13 years 8 months ago
Example-Based Learning for View-Based Human Face Detection
—We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns ...
Kah Kay Sung, Tomaso Poggio