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» Maximal Vector Computation in Large Data Sets
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ICML
2000
IEEE
14 years 10 months ago
Less is More: Active Learning with Support Vector Machines
We describe a simple active learning heuristic which greatly enhances the generalization behavior of support vector machines (SVMs) on several practical document classification ta...
Greg Schohn, David Cohn
VISSYM
2004
13 years 10 months ago
TimeHistograms for Large, Time-Dependent Data
Histograms are a very useful tool for data analysis, because they show the distribution of values over a data dimension. Many data sets in engineering (like computational fluid dy...
Robert Kosara, Fabian Bendix, Helwig Hauser
VLSID
2008
IEEE
83views VLSI» more  VLSID 2008»
14 years 9 months ago
Efficient Linear Macromodeling via Discrete-Time Time-Domain Vector Fitting
We present a discrete-time time-domain vector fitting algorithm, called TD-VFz, for rational function macromodeling of port-to-port responses with discrete time-sampled data. The ...
Chi-Un Lei, Ngai Wong

Presentation
945views
12 years 2 months ago
A Decentralized Method for Maximizing k-coverage Lifetime in WSNs
In this paper, we propose a decentralized method for maximizing lifetime of data collection wireless sensor networks (WSNs) by making minimal number of nodes operate and putting ot...
ICCAD
2000
IEEE
110views Hardware» more  ICCAD 2000»
14 years 1 months ago
Computing Phase Noise Eigenfunctions Directly from Steady-State Jacobian Matrices
The main effort in oscillator phase noise calculation lies in computing a vector function called the Perturbation Projection Vector (PPV). Current techniques for PPV calculation u...
Alper Demir, David E. Long, Jaijeet S. Roychowdhur...