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» An Instance Selection Approach to Multiple Instance Learning
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NCA
2007
IEEE
14 years 9 months ago
Using evolution to improve neural network learning: pitfalls and solutions
: Autonomous neural network systems typically require fast learning and good generalization performance, and there is potentially a trade-off between the two. The use of evolutiona...
John A. Bullinaria
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
14 years 8 months ago
Laplacian Spectrum Learning
Abstract. The eigenspectrum of a graph Laplacian encodes smoothness information over the graph. A natural approach to learning involves transforming the spectrum of a graph Laplaci...
Pannagadatta K. Shivaswamy, Tony Jebara
ESOP
2011
Springer
14 years 1 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...
BMVC
1997
14 years 11 months ago
Color Recognition by Learning: ATR in Color Images
Traditional methods for ATR Automatic Target Recognition use infrared IR sensors for detecting heat emanating fromtargets. IR-based ATR techniques are susceptible to sensor-in...
Shashi D. Buluswar, Bruce A. Draper
TON
2010
126views more  TON 2010»
14 years 4 months ago
MAC Scheduling With Low Overheads by Learning Neighborhood Contention Patterns
Aggregate traffic loads and topology in multi-hop wireless networks may vary slowly, permitting MAC protocols to `learn' how to spatially coordinate and adapt contention patte...
Yung Yi, Gustavo de Veciana, Sanjay Shakkottai