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NIPS
2004
13 years 11 months ago
2004
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
NIPS
2004
13 years 11 months ago
2004
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
NIPS
2004
13 years 11 months ago
2004
Theories of access consciousness address how it is that some mental states but not others are available for evaluation, choice behavior, and verbal report. Farah, O'Reilly, a...
NIPS
2004
13 years 11 months ago
2004
In many applications, good ranking is a highly desirable performance for a classifier. The criterion commonly used to measure the ranking quality of a classification algorithm is ...
NIPS
2004
13 years 11 months ago
2004
We propose a new interpretation of spiking neurons as Bayesian integrators accumulating evidence over time about events in the external world or the body, and communicating to oth...