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Now showing items 11-18 of 18
Sparse Representations for Fast, One-Shot Learning
(1997-11-01)
Humans rapidly and reliably learn many kinds of regularities and generalizations. We propose a novel model of fast learning that exploits the properties of sparse representations and the constraints imposed by a plausible ...
Proceedings of the Second PHANToM User's Group Workshop
(1997-12-01)
On October 19-22, 1997 the Second PHANToM Users Group Workshop was held at the MIT Endicott House in Dedham, Massachusetts. Designed as a forum for sharing results and insights, the workshop was attended by more than 60 ...
Translation Invariance in Object Recognition, and Its Relation to Other Visual Transformations
(1997-06-01)
Human object recognition is generally considered to tolerate changes of the stimulus position in the visual field. A number of recent studies, however, have cast doubt on the completeness of translation invariance. In a ...
Visual Recognition and Categorization on the Basis of Similarities to Multiple Class Prototypes
(1997-09-01)
To recognize a previously seen object, the visual system must overcome the variability in the object's appearance caused by factors such as illumination and pose. Developments in computer vision suggest that it may be ...
Belief Propagation and Revision in Networks with Loops
(1997-11-01)
Local belief propagation rules of the sort proposed by Pearl(1988) are guaranteed to converge to the optimal beliefs for singly connected networks. Recently, a number of researchers have empirically demonstrated good ...
Properties of Support Vector Machines
(1997-08-01)
Support Vector Machines (SVMs) perform pattern recognition between two point classes by finding a decision surface determined by certain points of the training set, termed Support Vectors (SV). This surface, which in some ...
Visual Segmentation without Classification in a Model of the Primary Visual Cortex
(1997-08-01)
Stimuli outside classical receptive fields significantly influence the neurons' activities in primary visual cortex. We propose that such contextual influences are used to segment regions by detecting the breakdown of ...
Estimating Dependency Structure as a Hidden Variable
(1997-06-01)
This paper introduces a probability model, the mixture of trees that can account for sparse, dynamically changing dependence relationships. We present a family of efficient algorithms that use EMand the Minimum Spanning ...