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ML
2010
ACM
193views Machine Learning» more  ML 2010»
13 years 2 months ago
On the eigenvectors of p-Laplacian
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...
Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping N...
ISHPC
2003
Springer
14 years 22 days ago
Evaluating Heuristic Scheduling Algorithms for High Performance Parallel Processing
Most cluster systems used in high performance computing do not allow process relocation at run-time. Finding an allocation that results in minimal completion time is NP-hard and (n...
Lars Lundberg, Magnus Broberg, Kamilla Klonowska
CVPR
2010
IEEE
13 years 10 months ago
Classification and Clustering via Dictionary Learning with Structured Incoherence
A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...
GECCO
2008
Springer
163views Optimization» more  GECCO 2008»
13 years 8 months ago
Embedded evolutionary multi-objective optimization for worst case robustness
In Multi-Objective Problems (MOPs) involving uncertainty, each solution might be associated with a cluster of performances in the objective space depending on the possible scenari...
Gideon Avigad, Jürgen Branke
BMCBI
2008
138views more  BMCBI 2008»
13 years 7 months ago
Methods for simultaneously identifying coherent local clusters with smooth global patterns in gene expression profiles
Background: The hierarchical clustering tree (HCT) with a dendrogram [1] and the singular value decomposition (SVD) with a dimension-reduced representative map [2] are popular met...
Yin-Jing Tien, Yun-Shien Lee, Han-Ming Wu, Chun-Ho...