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» Forecasting high-dimensional data
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ICDE
1998
IEEE
142views Database» more  ICDE 1998»
15 years 11 months ago
High Dimensional Similarity Joins: Algorithms and Performance Evaluation
Current data repositories include a variety of data types, including audio, images and time series. State of the art techniques for indexing such data and doing query processing r...
Nick Koudas, Kenneth C. Sevcik
ICML
1995
IEEE
15 years 10 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
ICDM
2008
IEEE
146views Data Mining» more  ICDM 2008»
15 years 4 months ago
Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets
Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive exp...
Meghana Deodhar, Joydeep Ghosh, Gunjan Gupta, Hyuk...
JMLR
2010
101views more  JMLR 2010»
14 years 4 months ago
Exploiting Feature Covariance in High-Dimensional Online Learning
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer...
STOC
1998
ACM
190views Algorithms» more  STOC 1998»
15 years 1 months ago
Efficient Search for Approximate Nearest Neighbor in High Dimensional Spaces
We address the problem of designing data structures that allow efficient search for approximate nearest neighbors. More specifically, given a database consisting of a set of vecto...
Eyal Kushilevitz, Rafail Ostrovsky, Yuval Rabani