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» Information-theoretic Competitive Learning
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ICML
2005
IEEE
14 years 10 months ago
Multi-way distributional clustering via pairwise interactions
We present a novel unsupervised learning scheme that simultaneously clusters variables of several types (e.g., documents, words and authors) based on pairwise interactions between...
Ron Bekkerman, Ran El-Yaniv, Andrew McCallum
SCIA
2005
Springer
186views Image Analysis» more  SCIA 2005»
14 years 3 months ago
Building Detection from Mobile Imagery Using Informative SIFT Descriptors
We propose reliable outdoor object detection on mobile phone imagery from off-the-shelf devices. With the goal to provide both robust object detection and reduction of computation...
Gerald Fritz, Christin Seifert, Manish Kumar, Luca...
ECAL
2007
Springer
14 years 1 months ago
Genotype Reuse More Important than Genotype Size in Evolvability of Embodied Neural Networks
odel of Embodiment on Abstract Systems: from Hierarchy to Heterarchy Kohei Nakajima, Soya Shinkai, Takashi Ikegami A Behavior-Based Model of the Hydra, Phylum Cnidaria Malin Aktius...
Chad W. Seys, Randall D. Beer
JMLR
2011
192views more  JMLR 2011»
13 years 4 months ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
KDD
2008
ACM
119views Data Mining» more  KDD 2008»
14 years 10 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen