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A Minimax Theorem with Applications to Machine Learning, Signal Processing, and Finance
convex optimization minimax theorem robust optimization
2015/7/9
This paper concerns a fractional function of the form x^Ta/sqrt{x^TBx}, where B is positive definite. We consider the game of choosing x from a convex set, to maximize the function, and choosing (a,B)...
Capturing Data Uncertainty in HighVolume Stream Processing
Data flow system data collection data modeling the sensor data
2014/12/24
We present the design and development of a data stream system that captures data uncertainty from data collection to query processing to final result generation. Our system focuses on data that is nat...
Gaussian Processes for Nonlinear Signal Processing
Gaussian Processes Nonlinear Signal Processing
2013/5/2
Gaussian processes (GPs) are versatile tools that have been successfully employed to solve nonlinear estimation problems in machine learning, but that are rarely used in signal processing. In this tut...
Computationally efficient algorithms for statistical image processing. Implementation in R
Image analysis signal detection image recon-struction percolation noisy image unsupervised machine learning spatial statistics
2011/3/24
In the series of our earlier papers on the subject, we proposed a novel statistical hypothesis testing method for detection of objects in noisy images. The method uses results from percolation theory ...
Online data processing: Comparison of Bayesian regularized particle filters
Online data processing Bayesian estimation regularized particle filters Stochastic Volatility models
2009/9/16
The aim of this paper is to compare three regularized particle filters in an online data processing context. We carry out the comparison in terms of hidden states filtering and parameter estimation, c...
Missing values：processing with the Kohonen algorithm
Missing values processing Kohonen algorithm
2010/4/26
Missing values：processing with the Kohonen algorithm。