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1,781
On the Power of the Adversary to Solve the Node Sampling Problem
 in "Transactions on LargeScale Data and KnowledgeCentered Systems (TLDKS
, 2013
"... Abstract. We study the problem of achieving uniform and fresh peer sampling in large scale dynamic systems under adversarial behaviors. Briefly, uniform and fresh peer sampling guarantees that any node in the system is equally likely to appear as a sample at any non malicious node in the system and ..."
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Cited by 4 (1 self)
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Abstract. We study the problem of achieving uniform and fresh peer sampling in large scale dynamic systems under adversarial behaviors. Briefly, uniform and fresh peer sampling guarantees that any node in the system is equally likely to appear as a sample at any non malicious node in the system
The Power of Convex Relaxation: NearOptimal Matrix Completion
, 2009
"... This paper is concerned with the problem of recovering an unknown matrix from a small fraction of its entries. This is known as the matrix completion problem, and comes up in a great number of applications, including the famous Netflix Prize and other similar questions in collaborative filtering. In ..."
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Cited by 359 (7 self)
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This paper is concerned with the problem of recovering an unknown matrix from a small fraction of its entries. This is known as the matrix completion problem, and comes up in a great number of applications, including the famous Netflix Prize and other similar questions in collaborative filtering
Application of theorem proving to problem solving
, 1969
"... This paper shows how an extension of the resolution proof procedure can be used to construct problem solutions. The extended proof procedure can solve problems involving state transformations. The paper explores several alternate problem representations and provides a discussion of solutions to samp ..."
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Cited by 264 (1 self)
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This paper shows how an extension of the resolution proof procedure can be used to construct problem solutions. The extended proof procedure can solve problems involving state transformations. The paper explores several alternate problem representations and provides a discussion of solutions
Characterizing the Adversarial Power in Uniform and Ergodic Node Sampling
, 2011
"... In this paper, we consider the problem of achieving uniform and ergodic peer sampling in large scale dynamic systems under adversarial behaviors. The main challenge is to guarantee that any honest node is able to construct a uniform and nonfixed (ergodic) sample of the node identifiers in the syste ..."
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Cited by 3 (2 self)
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In this paper, we consider the problem of achieving uniform and ergodic peer sampling in large scale dynamic systems under adversarial behaviors. The main challenge is to guarantee that any honest node is able to construct a uniform and nonfixed (ergodic) sample of the node identifiers
Hierarchical Bayesian Inference in the Visual Cortex
, 2002
"... this paper, we propose a Bayesian theory of hierarchical cortical computation based both on (a) the mathematical and computational ideas of computer vision and pattern the ory and on (b) recent neurophysiological experimental evidence. We ,2 have proposed that Grenander's pattern theory 3 coul ..."
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Cited by 300 (2 self)
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of Zhu and colleagues 7, 8 might be the most successful recent application of this proposal in solving real and difficult computer vision problems using generafive models, though its connection to the visual cortex has not been explored. Here, we bring in a powerful and widely applicable paradigm from
A Survey of Convergence Results on Particle Filtering Methods for Practitioners
, 2002
"... Optimal filtering problems are ubiquitous in signal processing and related fields. Except for a restricted class of models, the optimal filter does not admit a closedform expression. Particle filtering methods are a set of flexible and powerful sequential Monte Carlo methods designed to solve the o ..."
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Cited by 247 (8 self)
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Optimal filtering problems are ubiquitous in signal processing and related fields. Except for a restricted class of models, the optimal filter does not admit a closedform expression. Particle filtering methods are a set of flexible and powerful sequential Monte Carlo methods designed to solve
Transmission with energy harvesting nodes in fading wireless channels: Optimal policies
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 2011
"... Wireless systems comprised of rechargeable nodes have a significantly prolonged lifetime and are sustainable. A distinct characteristic of these systems is the fact that the nodes can harvest energy throughout the duration in which communication takes place. As such, transmission policies of the nod ..."
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Cited by 179 (46 self)
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directional waterfilling algorithm which provides a simple and concise interpretation of the necessary optimality conditions. We show the optimality of an adaptive directional waterfilling algorithm for the throughput maximization problem. We solve the transmission completion time minimization problem
A new approach for allocating buffers and bandwidth to heterogeneous, regulated traffic in an ATM node
 IEEE Journal on Selected Areas in Communications
, 1995
"... AbstractA new approach to determining the admissibility of variable bit rate (VBR) traffic in buffered digital networks is developed. In this approach all traffic presented to the network is assumed to have been subjected to leakybucket regulation, and extremal, periodic, onoff regulated traffic ..."
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Cited by 164 (10 self)
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. This leads to a singleresource statisticalmultiplexing problem which is solved using techniques previously used for unbuffered traffic. VBR traffic is found to be divisible into two classes, one for which statistical multiplexing is effective and one for which statistical multiplexing is ineffective
Learning in the Presence of Malicious Errors
 SIAM Journal on Computing
, 1993
"... In this paper we study an extension of the distributionfree model of learning introduced by Valiant [23] (also known as the probably approximately correct or PAC model) that allows the presence of malicious errors in the examples given to a learning algorithm. Such errors are generated by an advers ..."
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Cited by 184 (12 self)
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by an adversary with unbounded computational power and access to the entire history of the learning algorithm's computation. Thus, we study a worstcase model of errors. Our results include general methods for bounding the rate of error tolerable by any learning algorithm, efficient algorithms tolerating
Coil sensitivity encoding for fast MRI. In:
 Proceedings of the ISMRM 6th Annual Meeting,
, 1998
"... New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementa ..."
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Cited by 193 (3 self)
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complementary to Fourier preparation by linear field gradients. Thus, by using multiple receiver coils in parallel scan time in Fourier imaging can be considerably reduced. The problem of image reconstruction from sensitivity encoded data is formulated in a general fashion and solved for arbitrary coil
Results 1  10
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1,781