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Fundamental limits on the . . .
"... The MIX technique forms the basis of many popular services that offer anonymity of communication in open and shared networks such as the Internet. In this paper, fundamental limits on the anonymity provided by the MIX technique are found by considering two different settings. First, we consider an i ..."
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The MIX technique forms the basis of many popular services that offer anonymity of communication in open and shared networks such as the Internet. In this paper, fundamental limits on the anonymity provided by the MIX technique are found by considering two different settings. First, we consider
Some Fundamental Limits on Cognitive Radio
 in Fortysecond Allerton Conference on Communication, Control, and Computing
, 2004
"... Cognitive radio refers to wireless architectures in which a communication system does not operate in a fixed assigned band, but rather searches and finds an appropriate band in which to operate. In this paper we explore, from first principles, the fundamental requirements for such system that tries ..."
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Cited by 171 (15 self)
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Cognitive radio refers to wireless architectures in which a communication system does not operate in a fixed assigned band, but rather searches and finds an appropriate band in which to operate. In this paper we explore, from first principles, the fundamental requirements for such system that tries
Limits on fundamental limits to computation
 Nature
, 2014
"... An indispensable part of our lives, computing has also become essential to industries and governments. Steady improvements in computer hardware have been supported by periodic doubling of transistor densities in integrated circuits over the last fifty years. Such Moore scaling now requires increasin ..."
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Cited by 2 (0 self)
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increasingly heroic efforts, stimulating research in alternative hardware and stirring controversy. To help evaluate emerging technologies and enrich our understanding of integratedcircuit scaling, we review fundamental limits to computation: in manufacturing, energy, physical space, design and verification
Fundamental Limitations of Spectral Clustering
 in Advanced in Neural Information Processing Systems 19, B. Schölkopf and
, 2007
"... Spectral clustering methods are common graphbased approaches to clustering of data. Spectral clustering algorithms typically start from local information encoded in a weighted graph on the data and cluster according to the global eigenvectors of the corresponding (normalized) similarity matrix. One ..."
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Cited by 26 (4 self)
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. One contribution of this paper is to present fundamental limitations of this general local to global approach. We show that based only on local information, the normalized cut functional is not a suitable measure for the quality of clustering. Further, even with a suitable similarity measure, we show
Fundamental Limits for Information Retrieval
, 1999
"... The fundamental limits of performance for a general model of information retrieval from databases are studied. In the scenarios considered a large quantity of information is to be stored on some physical storage device. Requests for information are modeled as a randomly generated sequence with a kno ..."
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Cited by 2 (1 self)
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The fundamental limits of performance for a general model of information retrieval from databases are studied. In the scenarios considered a large quantity of information is to be stored on some physical storage device. Requests for information are modeled as a randomly generated sequence with a
1Fundamental Limits of Cooperation
"... Cooperation is viewed as a key ingredient for interference management in wireless systems. This paper shows that cooperation has fundamental limitations. The main result is that even full cooperation between transmitters cannot in general change an interferencelimited network to a noiselimited net ..."
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Cooperation is viewed as a key ingredient for interference management in wireless systems. This paper shows that cooperation has fundamental limitations. The main result is that even full cooperation between transmitters cannot in general change an interferencelimited network to a noiselimited
Spectrum Sensing: Fundamental Limits
"... Abstract Cognitive radio systems need to be able to robustly sense spectrum holes if they want to use spectrum opportunistically. However, this problem is more subtle than it first appears. It turns out that realworld uncertainties make it impossible to guarantee both robustness and highsensitivit ..."
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reasonable approximate metrics that capture the two desirable features of a spectrum sensor: safety to primary users and performance for the cognitive radios. It is the tradeoff between these two that is fundamental. Singleuser sensing turns out to have fundamental limits that require access to more
The fundamental limit theorems in probability
 Electron. J. Combin
, 1945
"... the mathematical content and meaning of the two most important limit theorems in the modern theory of probability: the central limit theorem 1 and the recently discovered precise form of what was generally ..."
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Cited by 23 (0 self)
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the mathematical content and meaning of the two most important limit theorems in the modern theory of probability: the central limit theorem 1 and the recently discovered precise form of what was generally
On the fundamental limits of adaptive sensing
, 2011
"... Suppose we can sequentially acquire arbitrary linear measurements of an ndimensional vector x resulting in the linear model y = Ax + z, where z represents measurement noise. If the signal is known to be sparse, one would expect the following folk theorem to be true: choosing an adaptive strategy wh ..."
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Cited by 25 (3 self)
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Suppose we can sequentially acquire arbitrary linear measurements of an ndimensional vector x resulting in the linear model y = Ax + z, where z represents measurement noise. If the signal is known to be sparse, one would expect the following folk theorem to be true: choosing an adaptive strategy which cleverly selects the next row of A based on what has been previously observed should do far better than a nonadaptive strategy which sets the rows of A ahead of time, thus not trying to learn anything about the signal in between observations. This paper shows that the folk theorem is false. We prove that the advantages offered by clever adaptive strategies and sophisticated estimation procedures—no matter how intractable—over classical compressed acquisition/recovery schemes are, in general, minimal.
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