As a baseline for software development, a correct and complete requirements definition is one foundation of software quality. Previously, a novel approach to static testing of sof...
When only a small number of labeled samples are available, supervised dimensionality reduction methods tend to perform poorly due to overfitting. In such cases, unlabeled samples ...
We present an extension of sparse PCA, or sparse dictionary learning, where the sparsity patterns of all dictionary elements are structured and constrained to belong to a prespeci...
Rodolphe Jenatton, Guillaume Obozinski, Francis Ba...
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Recently many data types arising from data mining and Web search applications can be modeled as bipartite graphs. Examples include queries and URLs in query logs, and authors and ...