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DAGSTUHL
2009
13 years 8 months ago
Learning Highly Structured Manifolds: Harnessing the Power of SOMs
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
Erzsébet Merényi, Kadim Tasdemir, Li...
WWW
2008
ACM
14 years 8 months ago
Graph theoretical framework for simultaneously integrating visual and textual features for efficient web image clustering
With the explosive growth of Web and the recent development in digital media technology, the number of images on the Web has grown tremendously. Consequently, Web image clustering...
Manjeet Rege, Ming Dong, Jing Hua
KDD
2008
ACM
159views Data Mining» more  KDD 2008»
14 years 8 months ago
Semi-supervised learning with data calibration for long-term time series forecasting
Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...
Haibin Cheng, Pang-Ning Tan
RECOMB
2005
Springer
14 years 7 months ago
Predicting Protein-Peptide Binding Affinity by Learning Peptide-Peptide Distance Functions
Many important cellular response mechanisms are activated when a peptide binds to an appropriate receptor. In the immune system, the recognition of pathogen peptides begins when th...
Chen Yanover, Tomer Hertz
SAC
2009
ACM
14 years 2 months ago
An empirical study of incorporating cost into test suite reduction and prioritization
Software developers use testing to gain and maintain confidence in the correctness of a software system. Automated reduction and prioritization techniques attempt to decrease the...
Adam M. Smith, Gregory M. Kapfhammer