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169
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ICML
1994
IEEE
15 years 9 months ago
Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms
With the goal of reducing computational costs without sacrificing accuracy, we describe two algorithms to find sets of prototypes for nearest neighbor classification. Here, the te...
David B. Skalak
UAI
1996
15 years 7 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
ICALT
2010
IEEE
15 years 7 months ago
Students' Perceptions of the Factors Leading to Unsuccessful Group Collaboration
A nationwide sample of university students completed a survey that asked questions about their perceptions of the factors that can cause problems which exist with online or general...
Shuangyan Liu, Mike Joy, Nathan Griffiths
GECCO
2008
Springer
261views Optimization» more  GECCO 2008»
15 years 7 months ago
SSNNS -: a suite of tools to explore spiking neural networks
We are interested in engineering smart machines that enable backtracking of emergent behaviors. Our SSNNS simulator consists of hand-picked tools to explore spiking neural network...
Heike Sichtig, J. David Schaffer, Craig B. Laramee
145
Voted
ICML
2010
IEEE
15 years 7 months ago
Clustering processes
The problem of clustering is considered, for the case when each data point is a sample generated by a stationary ergodic process. We propose a very natural asymptotic notion of co...
Daniil Ryabko