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» Efficient Discovery of Confounders in Large Data Sets
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ICML
2008
IEEE
16 years 7 months ago
Fast solvers and efficient implementations for distance metric learning
In this paper we study how to improve nearest neighbor classification by learning a Mahalanobis distance metric. We build on a recently proposed framework for distance metric lear...
Kilian Q. Weinberger, Lawrence K. Saul
VLDB
2007
ACM
179views Database» more  VLDB 2007»
16 years 6 months ago
Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data
Market analysis is a representative data analysis process with many applications. In such an analysis, critical numerical measures, such as profit and sales, fluctuate over time a...
Xiaolei Li, Jiawei Han
CVPR
2004
IEEE
15 years 10 months ago
Efficient Graphical Models for Processing Images
Graphical models are powerful tools for processing images. However, the large dimensionality of even local image data poses a difficulty: representing the range of possible graphi...
Marshall F. Tappen, Bryan C. Russell, William T. F...
JMLR
2010
134views more  JMLR 2010»
15 years 1 months ago
Using Contextual Representations to Efficiently Learn Context-Free Languages
We present a polynomial update time algorithm for the inductive inference of a large class of context-free languages using the paradigm of positive data and a membership oracle. W...
Alexander Clark, Rémi Eyraud, Amaury Habrar...
ICASSP
2011
IEEE
14 years 10 months ago
Ordering for energy efficient estimation and optimization in sensor networks
A discretized version of a continuous optimization problem is considered for the case where data is obtained from a set of dispersed sensor nodes and the overall metric is a sum o...
Rick S. Blum