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NIPS
2004
13 years 11 months ago
Limits of Spectral Clustering
An important aspect of clustering algorithms is whether the partitions constructed on finite samples converge to a useful clustering of the whole data space as the sample size inc...
Ulrike von Luxburg, Olivier Bousquet, Mikhail Belk...
SODA
2004
ACM
107views Algorithms» more  SODA 2004»
13 years 11 months ago
A note on the nearest neighbor in growth-restricted metrics
In this paper, we give results relevant to sequential and distributed dynamic data structures for finding nearest neighbors in growth-restricted metrics. Our sequential data struc...
Kirsten Hildrum, John Kubiatowicz, Sean Ma, Satish...
NIPS
2000
13 years 11 months ago
A Support Vector Method for Clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladi...
ARC
2007
Springer
152views Hardware» more  ARC 2007»
13 years 10 months ago
Statistical signal processing approaches to fault detection
: The parity space approach to fault detection and isolation (FDI) has been developed during the last twenty years, and the focus here is to describe its application to stochastic ...
Fredrik Gustafsson
CORR
2010
Springer
124views Education» more  CORR 2010»
13 years 10 months ago
Online Learning of Noisy Data with Kernels
We study online learning when individual instances are corrupted by adversarially chosen random noise. We assume the noise distribution is unknown, and may change over time with n...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...