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NIPS
2004
14 years 11 months ago
Maximising Sensitivity in a Spiking Network
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...
Anthony J. Bell, Lucas C. Parra
UM
2010
Springer
15 years 2 months ago
Modeling Individualization in a Bayesian Networks Implementation of Knowledge Tracing
The field of intelligent tutoring systems has been using the well known knowledge tracing model, popularized by Corbett and Anderson (1995) to track individual users’ knowledge f...
Zachary A. Pardos, Neil T. Heffernan
MICCAI
2010
Springer
14 years 8 months ago
Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis
The use of machine learning tools is gaining popularity in neuroimaging, as it provides a sensitive assessment of the information conveyed by brain images. In particular, finding ...
Vincent Michel, Evelyn Eger, Christine Keribin, Be...
IWLCS
2001
Springer
15 years 2 months ago
Explorations in LCS Models of Stock Trading
In previous papers we have described the basic elements for building an economic model consisting of a group of artificial traders functioning and adapting in an environment conta...
Sonia Schulenburg, Peter Ross
ICITS
2009
14 years 7 months ago
Survey: Leakage Resilience and the Bounded Retrieval Model
Abstract. This survey paper studies recent advances in the field of LeakageResilient Cryptography. This booming area is concerned with the design of cryptographic primitives resist...
Joël Alwen, Yevgeniy Dodis, Daniel Wichs