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Parameter Estimation from Quantized Observations in Multiplicative Noise Environments
, 2014
"... The problem of distributed parameter estimation from binary quantized observations is studied when the unquantized observations are corrupted by combined multiplicative and additive Gaussian noise. These results are applicable to sensor networks where the sensors observe a parameter in combined addi ..."
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The problem of distributed parameter estimation from binary quantized observations is studied when the unquantized observations are corrupted by combined multiplicative and additive Gaussian noise. These results are applicable to sensor networks where the sensors observe a parameter in combined
Quantization Index Modulation: A Class of Provably Good Methods for Digital Watermarking and Information Embedding
 IEEE TRANS. ON INFORMATION THEORY
, 1999
"... We consider the problem of embedding one signal (e.g., a digital watermark), within another "host" signal to form a third, "composite" signal. The embedding is designed to achieve efficient tradeoffs among the three conflicting goals of maximizing informationembedding rate, mini ..."
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Cited by 495 (15 self)
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, minimizing distortion between the host signal and composite signal, and maximizing the robustness of the embedding. We introduce new classes of embedding methods, termed quantization index modulation (QIM) and distortioncompensated QIM (DCQIM), and develop convenient realizations in the form of what we
ModelBased Clustering, Discriminant Analysis, and Density Estimation
 JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
, 2000
"... Cluster analysis is the automated search for groups of related observations in a data set. Most clustering done in practice is based largely on heuristic but intuitively reasonable procedures and most clustering methods available in commercial software are also of this type. However, there is little ..."
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Cited by 557 (28 self)
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for modelbased clustering that provides a principled statistical approach to these issues. We also show that this can be useful for other problems in multivariate analysis, such as discriminant analysis and multivariate density estimation. We give examples from medical diagnosis, mineeld detection, cluster
Just Relax: Convex Programming Methods for Identifying Sparse Signals in Noise
, 2006
"... This paper studies a difficult and fundamental problem that arises throughout electrical engineering, applied mathematics, and statistics. Suppose that one forms a short linear combination of elementary signals drawn from a large, fixed collection. Given an observation of the linear combination that ..."
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Cited by 496 (2 self)
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This paper studies a difficult and fundamental problem that arises throughout electrical engineering, applied mathematics, and statistics. Suppose that one forms a short linear combination of elementary signals drawn from a large, fixed collection. Given an observation of the linear combination
Preference Parameters And Behavioral Heterogeneity: An Experimental Approach In The Health And Retirement Study
, 1997
"... This paper reports measures of preference parameters relating to risk tolerance, time preference, and intertemporal substitution. These measures are based on survey responses to hypothetical situations constructed using an economic theorist's concept of the underlying parameters. The individual ..."
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Cited by 524 (12 self)
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. The individual measures of preference parameters display heterogeneity. Estimated risk tolerance and the elasticity of intertemporal substitution are essentially uncorrelated across individuals. Measured risk tolerance is positively related to risky behaviors, including smoking, drinking, failing to have
Diversity and Multiplexing: A Fundamental Tradeoff in Multiple Antenna Channels
 IEEE Trans. Inform. Theory
, 2002
"... Multiple antennas can be used for increasing the amount of diversity or the number of degrees of freedom in wireless communication systems. In this paper, we propose the point of view that both types of gains can be simultaneously obtained for a given multiple antenna channel, but there is a fund ..."
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Cited by 1143 (20 self)
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Multiple antennas can be used for increasing the amount of diversity or the number of degrees of freedom in wireless communication systems. In this paper, we propose the point of view that both types of gains can be simultaneously obtained for a given multiple antenna channel, but there is a
Estimating the Support of a HighDimensional Distribution
, 1999
"... Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We propo ..."
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Cited by 766 (29 self)
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Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We
Estimating Continuous Distributions in Bayesian Classifiers
 In Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence
, 1995
"... When modeling a probability distribution with a Bayesian network, we are faced with the problem of how to handle continuous variables. Most previous work has either solved the problem by discretizing, or assumed that the data are generated by a single Gaussian. In this paper we abandon the normality ..."
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Cited by 489 (2 self)
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distribution with a single Gaussian; and using nonparametric kernel density estimation. We observe large reductions in error on several natural and artificial data sets, which suggests that kernel estimation is a useful tool for learning Bayesian models. In Proceedings of the Eleventh Conference on Uncertainty
Coda: A Highly Available File System for a Distributed Workstation Environment
 In IEEE Transactions on Computers
, 1990
"... Abstract Coda is a file system for a largescale distributed computing environment composed of Unix workstations. It provides resiliency to server and network failures through the use of two distinct but complementary mechanisms. One mechanism, server replication,stores copies of a file at multiple ..."
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Cited by 530 (46 self)
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Abstract Coda is a file system for a largescale distributed computing environment composed of Unix workstations. It provides resiliency to server and network failures through the use of two distinct but complementary mechanisms. One mechanism, server replication,stores copies of a file
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