Results 1 -
3 of
3
Semi-rational Models of Conditioning: The Case of Trial Order
, 2007
"... Bayesian treatments of animal conditioning start from a generative model that specifies precisely a set of assumptions about the structure of the learning task. Optimal rules for learning are direct mathematical consequences of these assumptions. In terms of Marr’s (1982) levels of analyses, the mai ..."
Abstract
-
Cited by 3 (1 self)
- Add to MetaCart
Bayesian treatments of animal conditioning start from a generative model that specifies precisely a set of assumptions about the structure of the learning task. Optimal rules for learning are direct mathematical consequences of these assumptions. In terms of Marr’s (1982) levels of analyses, the main task at the computational level
Efficient Boundary Tracking Through Sampling
"... The proposed algorithm for image segmentation is inspired by an algorithm for autonomous environmental boundary tracking. The algorithm relies on a tracker that traverses a boundary between regions in a sinusoidal-like path. Boundary tracking is done by efficiently sampling points, resulting in a si ..."
Abstract
- Add to MetaCart
The proposed algorithm for image segmentation is inspired by an algorithm for autonomous environmental boundary tracking. The algorithm relies on a tracker that traverses a boundary between regions in a sinusoidal-like path. Boundary tracking is done by efficiently sampling points, resulting in a significant savings in computation time. Page’s cumulative sum (CUSUM) procedure and other methods are adapted to handle a high level of noise. Applications to large data sets such as hyperspectral are of particular interest. Irregularly shaped boundaries such as fractals are also treated at very fine detail.
