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» An Instance Selection Approach to Multiple Instance Learning
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NCA
2007
IEEE
15 years 2 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»
15 years 1 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 6 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
15 years 4 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 10 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