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» A Theory for Memory-Based Learning
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NIPS
2008
15 years 7 months ago
Posterior Consistency of the Silverman g-prior in Bayesian Model Choice
Kernel supervised learning methods can be unified by utilizing the tools from regularization theory. The duality between regularization and prior leads to interpreting regularizat...
Zhihua Zhang, Michael I. Jordan, Dit-Yan Yeung
ENTCS
2006
103views more  ENTCS 2006»
15 years 6 months ago
Static Equivalence is Harder than Knowledge
There are two main ways of defining secrecy of cryptographic protocols. The first version checks if the adversary can learn the value of a secret parameter. In the second version,...
Johannes Borgström
SIGCSE
2008
ACM
132views Education» more  SIGCSE 2008»
15 years 6 months ago
Course experiences of computing students with disabilities: four case studies
Inclusive education is the practice of making sure that all students of all abilities have positive learning experiences. The study presented in this paper explores the current st...
Katherine Deibel
NN
1998
Springer
112views Neural Networks» more  NN 1998»
15 years 6 months ago
Continuous attractors and oculomotor control
A recurrent neural network can possess multiple stable states, a property that many brain theories have implicated in learning and memory. There is good evidence for such multista...
H. Sebastian Seung
EMNLP
2009
15 years 4 months ago
A Simple Unsupervised Learner for POS Disambiguation Rules Given Only a Minimal Lexicon
We propose a new model for unsupervised POS tagging based on linguistic distinctions between open and closed-class items. Exploiting notions from current linguistic theory, the sy...
Qiuye Zhao, Mitch Marcus