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NIPS
2007
15 years 7 months ago
A neural network implementing optimal state estimation based on dynamic spike train decoding
It is becoming increasingly evident that organisms acting in uncertain dynamical environments often employ exact or approximate Bayesian statistical calculations in order to conti...
Omer Bobrowski, Ron Meir, Shy Shoham, Yonina C. El...
CORR
1998
Springer
125views Education» more  CORR 1998»
15 years 6 months ago
Automating Coreference: The Role of Annotated Training Data
Wereporthere ona studyof interannotatoragreementin the coreferencetask as defined by the MessageUnderstanding Conference(MUC-6and MUC-7).Basedon feedback from annotators, weclarif...
Lynette Hirschman, Patricia Robinson, John D. Burg...
ICASSP
2011
IEEE
14 years 10 months ago
A kernelized maximal-figure-of-merit learning approach based on subspace distance minimization
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
Byungki Byun, Chin-Hui Lee
KDD
2009
ACM
204views Data Mining» more  KDD 2009»
16 years 6 months ago
Improving classification accuracy using automatically extracted training data
Classification is a core task in knowledge discovery and data mining, and there has been substantial research effort in developing sophisticated classification models. In a parall...
Ariel Fuxman, Anitha Kannan, Andrew B. Goldberg, R...
BMCBI
2005
108views more  BMCBI 2005»
15 years 6 months ago
A linear memory algorithm for Baum-Welch training
Background: Baum-Welch training is an expectation-maximisation algorithm for training the emission and transition probabilities of hidden Markov models in a fully automated way. I...
István Miklós, Irmtraud M. Meyer