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366
Breaking Spectrum Gridlock with Cognitive Radios: An Information Theoretic Perspective
, 2008
"... Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. This paper surveys the fundamental capacity limits and associated transmission techniques for different wireless network design paradigms based on this promising technology. These paradigms are unified b ..."
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Cited by 265 (4 self)
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summary of the known capacity characterizations in terms of upper and lower bounds for each of these three approaches. The increase in system degrees of freedom obtained through cognitive radios is also illuminated. This information theoretic survey provides guidelines for the spectral efficiency gains
Simulating Normalized Constants: From Importance Sampling to Bridge Sampling to Path Sampling
, 1998
"... Computing (ratios of) normalizing constants of probability models is a fundamental computational problem for many statistical and scientific studies. Monte Carlo simulation is an effective technique, especially with complex and high-dimensional models. This paper aims to bring to the attention of ..."
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Cited by 233 (5 self)
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efficiency to thermodynamic integration, and the search of optimal paths turns out to have close connections with the Jeffreys prior density and the Rao and Hellinger distances between two densities. We provide an informative theoretical example as well as two empirical examples (involving 17- to 70
Boosting efficiency and security in proof of ownership for deduplication
- in Proceedings of the 7th ACM Symposium on Information, Computer and Communications Security, ser. ASIACCS ’12
"... Deduplication is a technique used to reduce the amount of storage needed by service providers. It is based on the intuition that several users may want (for different reasons) to store the same content. Hence, storing a single copy of these files is sufficient. Albeit simple in theory, the implement ..."
Abstract
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Cited by 13 (1 self)
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introduce a novel Proof of Ownership (POW) scheme that has all features of the state-of-the-art solution while incurring only a fraction of the overhead experienced by the competitor; second, the security of the proposed mechanisms relies on information theoretical (combinatoric) rather than computational
Causality discovery with additive disturbances: An information-theoretical perspective
- In Machine Learning and Knowledge Discovery in Databases
, 2009
"... Abstract. We consider causally sufficient acyclic causal models in which the relationship among the variables is nonlinear while disturbances have linear effects, and show that three principles, namely, the causal Markov condition (together with the independence between each disturbance and the corr ..."
Abstract
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Cited by 4 (1 self)
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and the corresponding parents), minimum disturbance entropy, and mutual independence of the disturbances, are equivalent. This motivates new and more efficient methods for some causal discovery problems. In particular, we propose to use multichannel blind deconvolution, an extension of independent component analysis
Boosting contextual information in contentbased image retrieval
- In the 6th ACM SIGMM international workshop on Multimedia information retrieval, 31–38. ANKERST
, 1999
"... We present a new framework for characterizing and retrieving objects in cluttered scenes. This CBIR system is based on a new representation describing every object taking into account the local properties of its parts and their mutual spatial relations, without relying on accurate segmentation. For ..."
Abstract
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Cited by 6 (1 self)
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. For this purpose, a new multi-dimensional histogram is used that measures the joint distribution of local properties and relative spatial positions. Instead of using a single descriptor for all the image, we represent the image by a set of histograms covering the object from different perspectives. We integrate
Boosting Contextual Information in Content-Based Image Retrieval
"... We present a new framework for characterizing and retrieving objects in cluttered scenes. This CBIR system is based on a new representation describing everyobject taking into account the local properties of its parts and their mutual spatial relations, without relying on accurate segmentation. For t ..."
Abstract
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. For this purpose, a new multi-dimensional histogram is used that measures the joint distribution of local properties and relative spatial positions. Instead of using a single descriptor for all the image, we represent the image bya set of histograms covering the object from different perspectives. We integrate
Boosting Contextual Information in Content-Based Image Retrieval
"... We present a new framework for characterizing and retriev-ing objects in cluttered scenes. This CBIR system is based on a new representation describing every object taking into account the local properties of its parts and their mutual spatial relations, without relying on accurate segmentation. For ..."
Abstract
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. For this purpose, a new multi-dimensional histogram is used that measures the joint distribution of local properties and relative spatial positions. Instead of using a single descrip-tor for all the image, we represent the image by a set of histograms covering the object from different perspectives. We integrate
PERSPECTIVE
"... Call centres in the police force are restrictive information systems which tend to present call operators with constraints that they need to overcome using their experience in order to offer better services to the public. This paper is looking at how elements of human agency come in to play and help ..."
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in practice. We use empirical data from contact centres and operational rooms of five UK police forces. After extensive observations we present how police call handlers manipulate digital information efficiently through human agency. The theoretical framework is based on the three elements of agency theory
Boosting with Structure Information in the Functional Space: an Application to Graph Classification
"... Boosting is a very successful classification algorithm that produces a linear combination of “weak ” classifiers (a.k.a. base learners) to obtain high quality classification models. In this paper we propose a new boosting algorithm where base learners have structure relationships in the functional s ..."
Abstract
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Cited by 7 (1 self)
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have derived efficient optimization algorithms based on coordinate decent for the new boosting formulation and theoretically prove that it exhibits a natural grouping effect for nearby spatial or overlapping features. Using comprehensive experimental study, we have demonstrated the effectiveness
Performance vs Computational Efficiency for Optimizing Single and Dynamic MRFs: Setting the State of the Art with Primal Dual Strategies
"... In this paper we introduce a novel method to address minimization of static and dynamic MRFs. Our approach is based on principles from linear programming and, in particular, on primal dual strategies. It generalizes prior state-of-the-art methods such as α-expansion, while it can also be used for ef ..."
Abstract
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Cited by 68 (25 self)
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for efficiently minimizing NP-hard problems with complex pair-wise potential functions. Furthermore, it offers a substantial speedup- of a magnitude ten- over existing techniques, due to the fact that it exploits information coming not only from the original MRF problem, but also from a dual one. The proposed
Results 1 - 10
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366
