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Adaptive Non-myopic Quantizer Design for Target Tracking in Wireless Sensor Networks
Adaptive Non-myopic Quantizer Design Target Tracking Wireless Sensor Networks
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2013/4/27
In this paper, we investigate the problem of non-myopic (multi-step ahead) quantizer design for target tracking using a wireless sensor network. Adopting the alternative conditional posterior Cramer-R...
Real-time On/Off-Road GPS Tracking
Vehicle Tracking GPS Particle Filtering Particle Learning
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2013/4/27
This document details the construction of a model for tracking a position and velocity state from GPS observations, with the intention of efficient, parallel online learning of state-dependent paramet...
Poly-Omic Prediction of Complex Traits: OmicKriging
Poly-Omic Prediction Complex Traits OmicKriging
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2013/4/27
High-confidence prediction of complex traits such as disease risk or drug response is an ultimate goal of personalized medicine. Although genome-wide association studies have discovered thousands of w...
Bandlimited Signal Reconstruction From the Distribution of Unknown Sampling Locations
Bandlimited Signal Reconstruction the Distribution Unknown Sampling Locations
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2013/4/28
We study the reconstruction of bandlimited fields from samples taken at unknown but statistically distributed sampling locations. The setup is motivated by distributed sampling where precise knowledge...
The cost of using exact confidence intervals for a binomial proportion
Asymptotic expansion binomial distribution expected length sample size determination proportion
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2013/4/27
When computing a confidence interval for a binomial proportion p one must choose between using an exact interval, which has a coverage probability of at least 1-{\alpha} for all values of p, and a sho...
Quantile-based classifiers
median-based classifier high-dimensional data misclassification rate skewness
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2013/4/27
Quantile classifiers for potentially high-dimensional data are defined by classifying an observation according to a sum of appropriately weighted component-wise distances of the components of the obse...
An Equivalence between the Lasso and Support Vector Machines
Equivalence the Lasso Support Vector Machines
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2013/4/28
We investigate the relation of two fundamental tools in machine learning, that is the support vector machine (SVM) for classification, and the Lasso technique used in regression. We show that the resu...
Analysis of Partially Observed Networks via Exponential-family Random Network Models
Analysis Partially Observed Networks via Exponential-family Random Network Models
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2013/4/27
Exponential-family random network (ERN) models specify a joint representation of both the dyads of a network and nodal characteristics. This class of models allow the nodal characteristics to be model...
Multivariate Temporal Dictionary Learning for EEG
Dictionary learning orthogonal matching pursuit multivariate shift-invariance EEG evoked potentials P300
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2013/4/28
This article addresses the issue of representing electroencephalographic (EEG) signals in an efficient way. While classical approaches use a fixed Gabor dictionary to analyze EEG signals, this article...
Hybrid Maximum Likelihood Modulation Classification Using Multiple Radios
Modulation classification data fusion ML esti-mation EM algorithm
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2013/4/28
The performance of a modulation classifier is highly sensitive to channel signal-to-noise ratio (SNR). In this paper, we focus on amplitude-phase modulations and propose a modulation classification fr...
Denoising Deep Neural Networks Based Voice Activity Detection
Deep learning denoising deep neural net-works voice activity detection
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2013/4/28
Recently, the deep-belief-networks (DBN) based voice activity detection (VAD) has been proposed. It is powerful in fusing the advantages of multiple features, and achieves the state-of-the-art perform...
On asymptotically optimal confidence regions and tests for high-dimensional models
asymptotically optimal confidence regions tests for high-dimensional models
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2013/4/27
We propose a general method for constructing confidence intervals and statistical tests for single or low-dimensional components of a large parameter vector in a high-dimensional model. It can be easi...
Local Gaussian process approximation for large computer experiments
sequential design sequential updating active learning surrogate model emulator compactly supported covariance local kriging neighborhoods
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2013/4/27
We provide a new approach to approximate emulation of large computer experiments. By focusing expressly on desirable properties of the predictive equations, we derive a family of local sequential desi...
On a link between kernel mean maps and Fraunhofer diffraction, with an application to super-resolution beyond the diffraction limit
On a link between kernel mean maps Fraunhofer diffraction an application super-resolution beyond the diffraction limit
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2013/4/28
We establish a link between Fourier optics and a recent construction from the machine learning community termed the kernel mean map. Using the Fraunhofer approximation, it identifies the kernel with t...
Inverse Signal Classification for Financial Instruments
time-series classification signal analysis decision tree learning
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2013/4/28
The paper presents new machine learning methods: signal composition, which classifies time-series regardless of length, type, and quantity; and self-labeling, a supervised-learning enhancement. The pa...