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» Approximate Data Structures with Applications
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SDM
2007
SIAM
126views Data Mining» more  SDM 2007»
14 years 11 months ago
Nonlinear Dimensionality Reduction using Approximate Nearest Neighbors
Nonlinear dimensionality reduction methods often rely on the nearest-neighbors graph to extract low-dimensional embeddings that reliably capture the underlying structure of high-d...
Erion Plaku, Lydia E. Kavraki
SIGCSE
1999
ACM
93views Education» more  SIGCSE 1999»
15 years 2 months ago
Patterns for decoupling data structures and algorithms
In order to build a data structure that is extensible and reusable, it is necessary to decouple the intrinsic and primitive behavior of the structure from the application specific...
Dung Zung Nguyen, Stephen B. Wong
MICRO
2009
IEEE
326views Hardware» more  MICRO 2009»
15 years 4 months ago
DDT: design and evaluation of a dynamic program analysis for optimizing data structure usage
Data structures define how values being computed are stored and accessed within programs. By recognizing what data structures are being used in an application, tools can make app...
Changhee Jung, Nathan Clark
KDD
2009
ACM
364views Data Mining» more  KDD 2009»
15 years 10 months ago
Causality quantification and its applications: structuring and modeling of multivariate time series
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
Takashi Shibuya, Tatsuya Harada, Yasuo Kuniyoshi
PODS
2008
ACM
159views Database» more  PODS 2008»
15 years 10 months ago
Approximation algorithms for clustering uncertain data
There is an increasing quantity of data with uncertainty arising from applications such as sensor network measurements, record linkage, and as output of mining algorithms. This un...
Graham Cormode, Andrew McGregor