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» Randomness, Stochasticity and Approximations
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BMCBI
2007
160views more  BMCBI 2007»
13 years 9 months ago
Identifying protein complexes directly from high-throughput TAP data with Markov random fields
Background: Predicting protein complexes from experimental data remains a challenge due to limited resolution and stochastic errors of high-throughput methods. Current algorithms ...
Wasinee Rungsarityotin, Roland Krause, Arno Sch&ou...
DKE
2007
130views more  DKE 2007»
13 years 9 months ago
Enabling access-privacy for random walk based data analysis applications
Random walk graph and Markov chain based models are used heavily in many data and system analysis domains, including web, bioinformatics, and queuing. These models enable the desc...
Ping Lin, K. Selçuk Candan
MOR
2010
118views more  MOR 2010»
13 years 7 months ago
Strategyproof Approximation of the Minimax on Networks
We consider the problem of locating a facility on a network, represented by a graph. A set of strategic agents have different ideal locations for the facility; the cost of an age...
Noga Alon, Michal Feldman, Ariel D. Procaccia, Mos...
FOCS
2008
IEEE
14 years 3 months ago
On the Value of Multiple Read/Write Streams for Approximating Frequency Moments
We consider the read/write streams model, an extension of the standard data stream model in which an algorithm can create and manipulate multiple read/write streams in addition to...
Paul Beame, Dang-Trinh Huynh-Ngoc
EMMCVPR
2005
Springer
14 years 2 months ago
Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...
Sanjiv Kumar, Jonas August, Martial Hebert