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MM
2004
ACM
167views Multimedia» more  MM 2004»
14 years 1 months ago
Learning an image manifold for retrieval
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
Xiaofei He, Wei-Ying Ma, HongJiang Zhang
SIAMCO
2002
71views more  SIAMCO 2002»
13 years 8 months ago
Rate of Convergence for Constrained Stochastic Approximation Algorithms
There is a large literature on the rate of convergence problem for general unconstrained stochastic approximations. Typically, one centers the iterate n about the limit point then...
Robert Buche, Harold J. Kushner
ML
2002
ACM
140views Machine Learning» more  ML 2002»
13 years 8 months ago
A Probabilistic Framework for SVM Regression and Error Bar Estimation
In this paper, we elaborate on the well-known relationship between Gaussian Processes (GP) and Support Vector Machines (SVM) under some convex assumptions for the loss functions. ...
Junbin Gao, Steve R. Gunn, Chris J. Harris, Martin...
TSP
2008
115views more  TSP 2008»
13 years 6 months ago
The Estimation of Laplace Random Vectors in Additive White Gaussian Noise
This paper develops and compares the maximum a posteriori (MAP) and minimum mean-square error (MMSE) estimators for spherically contoured multivariate Laplace random vectors in add...
Ivan W. Selesnick
MICRO
2006
IEEE
127views Hardware» more  MICRO 2006»
14 years 2 months ago
A Predictive Performance Model for Superscalar Processors
Designing and optimizing high performance microprocessors is an increasingly difficult task due to the size and complexity of the processor design space, high cost of detailed si...
P. J. Joseph, Kapil Vaswani, Matthew J. Thazhuthav...