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TIT
2008
141views more  TIT 2008»
15 years 5 months ago
Dimensionality Reduction for Distributed Estimation in the Infinite Dimensional Regime
Distributed estimation of an unknown signal is a common task in sensor networks. The scenario usually envisioned consists of several nodes, each making an observation correlated wi...
Olivier Roy, Martin Vetterli
FOCS
2006
IEEE
16 years 1 days ago
On the Optimality of the Dimensionality Reduction Method
We investigate the optimality of (1+ )-approximation algorithms obtained via the dimensionality reduction method. We show that: • Any data structure for the (1 + )-approximate n...
Alexandr Andoni, Piotr Indyk, Mihai Patrascu
SIAMSC
2008
198views more  SIAMSC 2008»
15 years 5 months ago
Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
T. Bui-Thanh, Karen Willcox, Omar Ghattas
SIGMOD
2001
ACM
184views Database» more  SIGMOD 2001»
16 years 6 months ago
Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data....
Eamonn J. Keogh, Kaushik Chakrabarti, Sharad Mehro...
NIPS
2008
15 years 7 months ago
Diffeomorphic Dimensionality Reduction
This paper introduces a new approach to constructing meaningful lower dimensional representations of sets of data points. We argue that constraining the mapping between the high a...
Christian Walder, Bernhard Schölkopf