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» A Practical Method for the Sparse Resultant
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CVPR
2009
IEEE
15 years 2 months ago
Minimizing Sparse Higher Order Energy Functions of Discrete Variables
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...
ICML
2005
IEEE
14 years 8 months ago
Healing the relevance vector machine through augmentation
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Carl Edward Rasmussen, Joaquin Quiñonero Ca...
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
13 years 9 months ago
Less is More: Compact Matrix Decomposition for Large Sparse Graphs
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...
Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Falo...
NIPS
2008
13 years 9 months ago
Deflation Methods for Sparse PCA
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...
Lester Mackey
ISIWI
2000
13 years 9 months ago
Usability Engineering Methods for the Web: Results From a Usability Study
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...
Ilse Maria Harms, Werner Schweibenz