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» Missing Data Estimation Using Polynomial Kernels
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ICML
2007
IEEE
16 years 3 months ago
Multifactor Gaussian process models for style-content separation
We introduce models for density estimation with multiple, hidden, continuous factors. In particular, we propose a generalization of multilinear models using nonlinear basis functi...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
129
Voted
SIBGRAPI
2008
IEEE
15 years 9 months ago
Structural Matching of 2D Electrophoresis Gels using Graph Models
2D electrophoresis is a well known method for protein separation which is extremely useful in the field of proteomics. Each spot in the image represents a protein accumulation an...
Alexandre Noma, Alvaro Pardo, Roberto Marcondes Ce...
120
Voted
WCE
2007
15 years 3 months ago
A Dynamic Method for the Evaluation and Comparison of Imputation Techniques
— Imputation of missing data is important in many areas, such as reducing non-response bias in surveys and maintaining medical documentation. Estimating the uncertainty inherent ...
Norman Solomon, Giles Oatley, Kenneth McGarry
142
Voted
CODES
2007
IEEE
15 years 9 months ago
Compile-time decided instruction cache locking using worst-case execution paths
Caches are notorious for their unpredictability. It is difficult or even impossible to predict if a memory access results in a definite cache hit or miss. This unpredictability i...
Heiko Falk, Sascha Plazar, Henrik Theiling
194
Voted
VLSISP
2011
358views Database» more  VLSISP 2011»
14 years 9 months ago
Accelerating Machine-Learning Algorithms on FPGAs using Pattern-Based Decomposition
Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from superlinear increases in ...
Karthik Nagarajan, Brian Holland, Alan D. George, ...