1![Algorithmic Construction of Low-Discrepancy Point Sets via Dependent Randomized Rounding Benjamin Doerra , Michael Gnewuchb , Magnus Wahlstr¨oma a Max-Planck-Institut f¨ Algorithmic Construction of Low-Discrepancy Point Sets via Dependent Randomized Rounding Benjamin Doerra , Michael Gnewuchb , Magnus Wahlstr¨oma a Max-Planck-Institut f¨](https://www.pdfsearch.io/img/94dca08350c7ea4dbd4775f38eb5615c.jpg) | Add to Reading ListSource URL: www.numerik.uni-kiel.deLanguage: English - Date: 2010-04-08 11:28:07
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2![Notes on Randomized Algorithms CS: Fall 2014 James Aspnes:04 Notes on Randomized Algorithms CS: Fall 2014 James Aspnes:04](https://www.pdfsearch.io/img/b086eac40d92f8d09f0529020e351d98.jpg) | Add to Reading ListSource URL: cs-www.cs.yale.eduLanguage: English - Date: 2014-12-17 20:04:41
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3![Notes on Randomized Algorithms CS: Fall 2014 James Aspnes:04 Notes on Randomized Algorithms CS: Fall 2014 James Aspnes:04](https://www.pdfsearch.io/img/789e3162c28f755d73471158ffc90531.jpg) | Add to Reading ListSource URL: cs.yale.eduLanguage: English - Date: 2014-12-17 20:04:41
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4![Learning Influence Probabilities In Social Networks Amit Goyal Francesco Bonchi Laks V. S. Lakshmanan Learning Influence Probabilities In Social Networks Amit Goyal Francesco Bonchi Laks V. S. Lakshmanan](https://www.pdfsearch.io/img/9a2deb401259921e0c9394afc454120f.jpg) | Add to Reading ListSource URL: www.wsdm-conference.orgLanguage: English - Date: 2009-12-30 01:37:52
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5![Deriving greedy algorithms and Lagrangian-relaxation algorithms Neal E. Young February 16, 2007 Deriving greedy algorithms and Lagrangian-relaxation algorithms Neal E. Young February 16, 2007](https://www.pdfsearch.io/img/c078125e0408bc86272889970c965436.jpg) | Add to Reading ListSource URL: www.cs.ucr.eduLanguage: English - Date: 2008-04-29 13:22:24
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6![26. Derandomization Given a randomized algorithm A, a natural approach towards derandomizing it is to find a method for searching the associated sample space Ω for a good point ω with respect to a given input instanc 26. Derandomization Given a randomized algorithm A, a natural approach towards derandomizing it is to find a method for searching the associated sample space Ω for a good point ω with respect to a given input instanc](https://www.pdfsearch.io/img/02fa56cb564200f2d02f11d4c5eb854a.jpg) | Add to Reading ListSource URL: lovelace.thi.informatik.uni-frankfurt.deLanguage: English - Date: 2007-08-30 03:42:25
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7![Learning Influence Probabilities In Social Networks Amit Goyal Francesco Bonchi Laks V. S. Lakshmanan Learning Influence Probabilities In Social Networks Amit Goyal Francesco Bonchi Laks V. S. Lakshmanan](https://www.pdfsearch.io/img/5f9d6c64dd25a6b79775d1b0b8d09e82.jpg) | Add to Reading ListSource URL: snap.stanford.eduLanguage: English - Date: 2011-11-19 02:38:44
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8![Influential Nodes in a Diffusion Model for Social Networks ´ Tardos2? ? ? David Kempe1? , Jon Kleinberg2?? , and Eva 1 Influential Nodes in a Diffusion Model for Social Networks ´ Tardos2? ? ? David Kempe1? , Jon Kleinberg2?? , and Eva 1](https://www.pdfsearch.io/img/2987725d4e664d4aa8421724a383493f.jpg) | Add to Reading ListSource URL: www.cs.cornell.eduLanguage: English - Date: 2005-05-20 00:29:25
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9![JOURNAL OF ALGORJTHMS 7,[removed]) JOURNAL OF ALGORJTHMS 7,[removed])](https://www.pdfsearch.io/img/ec9799d86c8a3ec69ced33604495f0bd.jpg) | Add to Reading ListSource URL: www.tau.ac.ilLanguage: English - Date: 2010-04-12 04:28:18
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