Higher order energy functions have the ability to encode
high level structural dependencies between pixels, which
have been shown to be extremely powerful for image labeling
pro...
Carsten Rother (Microsoft Research Cambridge), Pus...
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Given a large sparse graph, how can we find patterns and anomalies? Several important applications can be modeled as large sparse graphs, e.g., network traffic monitoring, resea...
In analogy to the PCA setting, the sparse PCA problem is often solved by iteratively alternating between two subtasks: cardinality-constrained rank-one variance maximization and m...
The paper presents the results of a study on usability methods for evaluating Web sites. lt summarizes the "Heuristics for Web Communications," and reports the practical...