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CVPR
2009
IEEE
15 years 3 months ago
Learning a Distance Metric from Multi-instance Multi-label Data
Multi-instance multi-label learning (MIML) refers to the learning problems where each example is represented by a bag/collection of instances and is labeled by multiple labels. ...
Rong Jin (Michigan State University), Shijun Wang...
EDBT
2011
ACM
197views Database» more  EDBT 2011»
12 years 11 months ago
Symmetrizations for clustering directed graphs
Graph clustering has generally concerned itself with clustering undirected graphs; however the graphs from a number of important domains are essentially directed, e.g. networks of...
Venu Satuluri, Srinivasan Parthasarathy
KDD
2006
ACM
145views Data Mining» more  KDD 2006»
14 years 8 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
KDD
2006
ACM
129views Data Mining» more  KDD 2006»
14 years 8 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
GECCO
2006
Springer
152views Optimization» more  GECCO 2006»
13 years 11 months ago
A combinatorial genetic algorithm for the configuration of the 2dF/AAOmega spectrograph at the anglo-Australian observatory
To help unravel the structure of the universe, astronomers have developed systems which observe large clusters of objects at the same time. One such system is the 2-degree field s...
Steven Manos, Geraint Lewis