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NIPS
1994
13 years 10 months ago
Learning Stochastic Perceptrons Under k-Blocking Distributions
We present a statistical method that PAC learns the class of stochastic perceptrons with arbitrary monotonic activation function and weights wi {-1, 0, +1} when the probability d...
Mario Marchand, Saeed Hadjifaradji
BC
2002
91views more  BC 2002»
13 years 9 months ago
Mathematical formulations of Hebbian learning
Several formulations of correlation-based Hebbian learning are reviewed. On the presynaptic side, activity is described either by a firing rate or by presynaptic spike arrival. The...
Wulfram Gerstner, Werner M. Kistler
ACL
2009
13 years 7 months ago
Word or Phrase? Learning Which Unit to Stress for Information Retrieval
The use of phrases in retrieval models has been proven to be helpful in the literature, but no particular research addresses the problem of discriminating phrases that are likely ...
Young-In Song, Jung-Tae Lee, Hae-Chang Rim
ICIP
2009
IEEE
13 years 7 months ago
A food image recognition system with Multiple Kernel Learning
Since health care on foods is drawing people's attention recently, a system that can record everyday meals easily is being awaited. In this paper, we propose an automatic foo...
Taichi Joutou, Keiji Yanai
JMLR
2010
185views more  JMLR 2010»
13 years 4 months ago
Multiple Kernel Learning on the Limit Order Book
Simple features constructed from order book data for the EURUSD currency pair were used to construct a set of kernels. These kernels were used both individually and simultaneously...
Tristan Fletcher, Zakria Hussain, John Shawe-Taylo...