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» Structured metric learning for high dimensional problems
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ICML
2006
IEEE
14 years 8 months ago
Optimal kernel selection in Kernel Fisher discriminant analysis
In Kernel Fisher discriminant analysis (KFDA), we carry out Fisher linear discriminant analysis in a high dimensional feature space defined implicitly by a kernel. The performance...
Seung-Jean Kim, Alessandro Magnani, Stephen P. Boy...
VLSID
2009
IEEE
108views VLSI» more  VLSID 2009»
14 years 8 months ago
Metric Based Multi-Timescale Control for Reducing Power in Embedded Systems
Abstract--Digital control for embedded systems often requires low-power, hard real-time computation to satisfy high control-loop bandwidth, low latency, and low-power requirements....
Forrest Brewer, João Pedro Hespanha, Nitin ...
DATAMINE
2006
224views more  DATAMINE 2006»
13 years 7 months ago
Characteristic-Based Clustering for Time Series Data
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman
ICCS
2007
Springer
14 years 1 months ago
Hessian-Based Model Reduction for Large-Scale Data Assimilation Problems
Assimilation of spatially- and temporally-distributed state observations into simulations of dynamical systems stemming from discretized PDEs leads to inverse problems with high-di...
Omar Bashir, Omar Ghattas, Judith Hill, Bart G. va...
MICCAI
2009
Springer
14 years 9 months ago
Fast and Robust 3-D MRI Brain Structure Segmentation
We present a novel method for the automatic detection and segmentation of (sub-)cortical gray matter structures in 3-D magnetic resonance images of the human brain. Essentially, th...
Michael Wels, Yefeng Zheng, Gustavo Carneiro, M...