A Fast Learning Algorithm for Deep Belief Nets
We show how to use “complementary priors” to eliminate the explaining-away effects that make inference difficult in densely connected belief nets that have many hidden layers. U...
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2,707 publications
Inference from Iterative Simulation Using Multiple Sequences
The Gibbs sampler, the algorithm of Metropolis and similar iterative simulation methods are potentially very helpful for summarizing multivariate distributions. Used naively, ho...
The Art of Case Study Research
Introduction An Intensive Study of Case Study Research Methods The Unique Case Research Questions The Nature of Qualitative Research Data Gathering Analysis and Interpretation C...
Regularization Paths for Generalized Linear Models via Coordinate Descent
We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multi- nom...
A Survey of Corporate Governance
ABSTRACT This article surveys research on corporate governance, with special attention to the importance of legal protection of investors and of ownership concentration in corpo...
Density Estimation for Statistics and Data Analysis
Introduction. Survey of Existing Methods. The Kernel Method for Univariate Data. The Kernel Method for Multivariate Data. Three Important Methods. Density Estimation in Action.
RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models
Abstract Summary: RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies ...
Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
This paper considers the model problem of reconstructing an object from incomplete frequency samples. Consider a discrete-time signal f ∈ C N and a randomly chosen set of freque...
Normalized cuts and image segmentation
We propose a novel approach for solving the perceptual grouping problem in vision. Rather than focusing on local features and their consistencies in the image data, our approach...