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ICML
1995
IEEE
16 years 7 months ago
Visualizing High-Dimensional Structure with the Incremental Grid Growing Neural Network
Understanding high-dimensional real world data usually requires learning the structure of the data space. The structure maycontain high-dimensional clusters that are related in co...
Justine Blackmore, Risto Miikkulainen
VMCAI
2010
Springer
16 years 3 months ago
Shape Analysis of Low-Level C with Overlapping Structures
Abstract. Device drivers often keep data in multiple data structures simultaneously while embedding list or tree related records into the records containing the actual data; this r...
Jörg Kreiker, Helmut Seidl, Vesal Vojdani
FAW
2008
Springer
225views Algorithms» more  FAW 2008»
15 years 8 months ago
Versioning Tree Structures by Path-Merging
We propose path-merging as a refinement of techniques used to make linked data structures partially persistent. Path-merging supports bursts of operations between any two adjacent ...
Khaireel A. Mohamed, Tobias Langner, Thomas Ottman...
EMNLP
2007
15 years 7 months ago
Semi-Supervised Structured Output Learning Based on a Hybrid Generative and Discriminative Approach
This paper proposes a framework for semi-supervised structured output learning (SOL), specifically for sequence labeling, based on a hybrid generative and discriminative approach...
Jun Suzuki, Akinori Fujino, Hideki Isozaki
CSDA
2010
132views more  CSDA 2010»
15 years 6 months ago
Approximate low-rank factorization with structured factors
An approximate rank revealing factorization problem with structure constraints on the normalized factors is considered. Examples of structure, motivated by an application in micro...
Ivan Markovsky, Mahesan Niranjan