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» A Theory for Memory-Based Learning
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NIPS
2001
15 years 7 months ago
Probabilistic principles in unsupervised learning of visual structure: human data and a model
To find out how the representations of structured visual objects depend on the co-occurrence statistics of their constituents, we exposed subjects to a set of composite images wit...
Shimon Edelman, Benjamin P. Hiles, Hwajin Yang, Na...
METMBS
2003
255views Mathematics» more  METMBS 2003»
15 years 7 months ago
Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery
Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support system...
Constantin F. Aliferis, Ioannis Tsamardinos, Alexa...
AAAI
1998
15 years 7 months ago
Boosting in the Limit: Maximizing the Margin of Learned Ensembles
The "minimum margin" of an ensemble classifier on a given training set is, roughly speaking, the smallest vote it gives to any correct training label. Recent work has sh...
Adam J. Grove, Dale Schuurmans
ICASSP
2010
IEEE
15 years 6 months ago
Robust regression using sparse learning for high dimensional parameter estimation problems
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
ECSA
2010
Springer
15 years 6 months ago
Software ecosystems vs. natural ecosystems: learning from the ingenious mind of nature
The use of the term ecosystem in the context of extensible software platforms and third-party developers or user communities has made us ponder about the similarities between soft...
Deepak Dhungana, Iris Groher, Elisabeth Schluderma...