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» On the Learnability of Vector Spaces
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FMSD
2007
110views more  FMSD 2007»
14 years 9 months ago
Exploiting interleaving semantics in symbolic state-space generation
Symbolic techniques based on Binary Decision Diagrams (BDDs) are widely employed for reasoning about temporal properties of hardware circuits and synchronous controllers. However, ...
Gianfranco Ciardo, Gerald Lüttgen, Andrew S. ...
DATAMINE
1999
143views more  DATAMINE 1999»
14 years 9 months ago
Partitioning Nominal Attributes in Decision Trees
To find the optimal branching of a nominal attribute at a node in an L-ary decision tree, one is often forced to search over all possible L-ary partitions for the one that yields t...
Don Coppersmith, Se June Hong, Jonathan R. M. Hosk...
BMCBI
2011
14 years 4 months ago
Estimating developmental states of tumors and normal tissues using a linear time-ordered model
Background: Tumor cells are considered to have an aberrant cell state, and some evidence indicates different development states appearing in the tumorigenesis. Embryonic developme...
Bo Zhang, Beibei Chen, Tao Wu, Zhenyu Xuan, Xiaope...
CVPR
2009
IEEE
16 years 5 months ago
Learning Semantic Visual Vocabularies Using Diffusion Distance
In this paper, we propose a novel approach for learning generic visual vocabulary. We use diffusion maps to au-tomatically learn a semantic visual vocabulary from ab-undant quantiz...
Jingen Liu (University of Central Florida), Yang Y...
ALT
2006
Springer
15 years 6 months ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri