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» Combining Information using Hard Constraints
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102
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CCECE
2006
IEEE
15 years 6 months ago
Dynamic and Parallel Approaches to Optimal Evolutionary Tree Construction
Phylogenetic trees are commonly reconstructed based on hard optimization problems such as Maximum parsimony (MP) and Maximum likelihood (ML). Conventional MP heuristics for produc...
Anupam Bhattacharjee, Kazi Zakia Sultana, Zalia Sh...
113
Voted
EUROPAR
2007
Springer
15 years 4 months ago
Efficient Parallel Simulation of Large-Scale Neuronal Networks on Clusters of Multiprocessor Computers
To understand the principles of information processing in the brain, we depend on models with more than 105 neurons and 109 connections. These networks can be described as graphs o...
Hans E. Plesser, Jochen M. Eppler, Abigail Morriso...
DEXAW
2010
IEEE
181views Database» more  DEXAW 2010»
15 years 1 months ago
Bridging the Gap between Heterogeneous and Semantically Diverse Content of Different Disciplines
The Web has been flooded with highly heterogeneous data sources that freely offer their data to the public. Careful design and compliance to standards is a way to cope with the he...
Siarhei Bykau, Nadzeya Kiyavitskaya, Chrisa Tsinar...
ICDM
2010
IEEE
128views Data Mining» more  ICDM 2010»
14 years 10 months ago
User-Based Active Learning
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
Christin Seifert, Michael Granitzer
130
Voted
MLMTA
2007
15 years 1 months ago
Consensus Based Ensembles of Soft Clusterings
— Cluster Ensembles is a framework for combining multiple partitionings obtained from separate clustering runs into a final consensus clustering. This framework has attracted mu...
Kunal Punera, Joydeep Ghosh