Publications
Explore 486 academic publications
Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
One of the central problems in machine learning and pattern recognition is to develop appropriate representations for complex data. We consider the problem of constructing a rep...
Homo Sacer
One of Italy's most original philosophers aims to connect the problem of pure possibility, potentiality, and power with the problem of political and social ethics in a context w...
Honeycomb Carbon: A Review of Graphene
ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTHoneycomb Carbon: A Review of GrapheneMatthew J. Allen†, Vincent C. Tung‡, and Richard B. Kaner*†‡View Author Information Department o...
Toward defining the preclinical stages of Alzheimer's disease: Recommendations from the National Institute on Aging‐Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease
The pathophysiological process of Alzheimer's disease (AD) is thought to begin many years before the diagnosis of AD dementia. This long “preclinical” phase of AD would provide ...
Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials
Funnel plots, and tests for funnel plot asymmetry, have been widely used to examine bias in the results of meta-analyses. Funnel plot asymmetry should not be equated with public...
Planetary Boundaries: Exploring the Safe Operating Space for Humanity
"Anthropogenic pressures on the Earth System have reached a scale where abrupt global environmental change can no longer be excluded. We propose a new approach to global sustain...
Power-law distributions in empirical data
Power-law distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and man-made phenomena. Unfortunately,...
Anarchy, State, and Utopia
Robert Nozicka s Anarchy, State, Utopia is a powerful, philosophical challenge to the most widely held political social positions of our age ---- liberal, socialist conservat...
Improving neural networks by preventing co-adaptation of feature detectors
When a large feedforward neural network is trained on a small training set, it typically performs poorly on held-out test data. This "overfitting" is greatly reduced by randomly...