Filters








20 Hits in 2.2 sec

Beyond Worst-case (In)approximability of Nonsubmodular Influence Maximization

Grant Schoenebeck, Biaoshuai Tao
2019 ACM Transactions on Computation Theory  
It admits a (1-1/e)-factor approximation algorithm if the influence function is submodular. Otherwise, in the worst case, the problem is NP-hard to approximate to within a factor of N^1-ε.  ...  This result also indicates that the "threshold" between submodularity and nonsubmodularity is sharp, regarding the approximability of influence maximization.  ...  Before our results there was some hope that the hardness of nonsubmodular influence maximization was only caused by the hardness of detecting community structure within the network.  ... 
doi:10.1145/3313904 fatcat:6yjd4oujlbap3mwopxcragsati

Don't Be Greedy: Leveraging Community Structure to Find High Quality Seed Sets for Influence Maximization [chapter]

Rico Angell, Grant Schoenebeck
2017 Lecture Notes in Computer Science  
We consider the problem of maximizing the spread of influence in a social network by choosing a fixed number of initial seeds -a central problem in the study of network cascades.  ...  We also present "worst-case" theoretical results proving that in certain settings our algorithm outputs seed sets that are a factor of Θ( √ n) more influential than those of the greedy algorithm, where  ...  Unfortunately, empirical research shows that most cascades are non-submodular [40, 3, 29] , and in this case little is known about InfluenceMaximization other than worst-case hardness.  ... 
doi:10.1007/978-3-319-71924-5_2 fatcat:6k3lduauq5h4rfl5nchgm45eyq

Efficient Algorithms for Monotone Non-Submodular Maximization with Partition Matroid Constraint [article]

Lan N. Nguyen, My T. Thai
2022 arXiv   pre-print
In this work, we study the problem of monotone non-submodular maximization with partition matroid constraint.  ...  We further investigate those algorithms' performance in two applications: Boosting Influence Spread and Video Summarization.  ...  Acknowledgements This work was supported in part by the National Science Foundation (NSF) grants IIS-1908594, CNS-1814614. We would like to thank the anonymous reviewers for their helpful feedback.  ... 
arXiv:2204.13832v1 fatcat:acoktyn7rvfnvkjfr6mmmuv7ny

Multiplex Influence Maximization in Online Social Networks with Heterogeneous Diffusion Models [article]

Alan Kuhnle, Md Abdul Alim, Xiang Li, Huiling Zhang, My T. Thai
2018 arXiv   pre-print
case, we formulate ISF, the greedy algorithm with approximation ratio (1 - 1/e).  ...  KSN takes an α-approximation algorithm A for the influence maximization problem on a single-layer network as input, and has approximation ratio (1-ϵ)α/(o+1)k for arbitrary ϵ > 0, o is the number of overlapping  ...  APPROXIMATIONS OF MIM Since influence maximization on a single network is a special case of influence maximization on a multiplex, MIM is N P -complete.  ... 
arXiv:1802.01729v1 fatcat:2vl6ndxri5bmhbmbbegvls3l7u

Don't Be Greedy: Leveraging Community Structure to Find High Quality Seed Sets for Influence Maximization [article]

Rico Angell, Grant Schoenebeck
2016 arXiv   pre-print
We consider the problem of maximizing the spread of influence in a social network by choosing a fixed number of initial seeds --- a central problem in the study of network cascades.  ...  We also present "worst-case" theoretical results proving that in certain settings our algorithm outputs seed sets that are a factor of Θ(√(n)) more influential than those of the greedy algorithm, where  ...  Unfortunately, empirical research shows that most cascades are non-submodular [40, 3, 29] , and in this case little is known about InfluenceMaximization other than worst-case hardness.  ... 
arXiv:1609.06520v1 fatcat:gqluq5qnpbhr7ahlu63jbf7ose

Influence Maximization Under Generic Threshold-based Non-submodular Model [article]

Liang Ma
2020 arXiv   pre-print
In other words, there is still a lack of efficient methods that can directly resolve non-submodular influence maximization problems.  ...  To the best of our knowledge, this is the first graph-based approach that directly tackles non-submodular influence maximization.  ...  ., we get G), to maintain the full influenceability in G, the worst case is that v 2 is selected as a seed node while all other seed nodes remain unchanged. Thus, |S * G | − |S * G ′ | ≤ 1.  ... 
arXiv:2012.12309v1 fatcat:gn7b5az6xvf2vh5cmkv5cutroy

Conditional Reliability in Uncertain Graphs [article]

Arijit Khan, Francesco Bonchi, Francesco Gullo, Andreas Nufer
2018 arXiv   pre-print
In particular, we study the problem of determining the k conditions that maximize the reliability between two nodes.  ...  In social influence networks the probability that a tweet of some user will be re-tweeted by her followers depends on whether the tweet contains specific hashtags.  ...  Assuming that P contains at least one path having less than k catalysts, then in the worst case the approximation ratio is ≥ 1 KC ≥ 1 r (where r is the total number of paths in the top-r path set P).  ... 
arXiv:1608.04474v3 fatcat:xjs2kxiugvd73oiw757oxu2way

From competition to complementarity

Wei Lu, Wei Chen, Laks V. S. Lakshmanan
2015 Proceedings of the VLDB Endowment  
We study two natural optimization problems, Self Influence Maximization and Complementary Influence Maximization, in a novel setting with complementary entities.  ...  The applicability of both techniques extends beyond our model and problems.  ...  This research is supported in part by a Discovery grant and a Discovery Accelerator Supplements grant from the Natural Sciences and Engineering Research Council of Canada (NSERC).  ... 
doi:10.14778/2850578.2850581 fatcat:lhcdfh4v4zcwxk6puhzjonoxye

Phrase-based Compressive Cross-Language Summarization

Jin-ge Yao, Xiaojun Wan, Jianguo Xiao
2015 Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing  
The task of cross-language document summarization is to create a summary in a target language from documents in a different source language.  ...  We design a greedy algorithm to approximately optimize the score function.  ...  This work was supported by National Hi-Tech Research and Development Program (863 Program) of China (2015AA015403, 2014AA015102) and National Natural Science Foundation of China (61170166, 61331011).  ... 
doi:10.18653/v1/d15-1012 dblp:conf/emnlp/YaoWX15 fatcat:3m5fdzyblzak7otr7gkgwzvozi

Transformation of General Binary MRF Minimization to the First-Order Case

H Ishikawa
2011 IEEE Transactions on Pattern Analysis and Machine Intelligence  
We also show that some minimization methods can be considered special cases of the present framework, as well as comparing the new method experimentally with other such techniques.  ...  Moreover, we formalize a framework for approximately minimizing higher-order multilabel MRF energies that combines the new reduction with the fusion-move and QPBO algorithms.  ...  This work was partially supported by the Kayamori Foundation and the Grant-in-Aid for Scientific Research 19650065 from the Japan Society for the Promotion of Science.  ... 
doi:10.1109/tpami.2010.91 pmid:20421673 fatcat:vchkur2jo5ab5adcrnxz7ywzcm

EPIC: Welfare Maximization under Economically Postulated Independent Cascade Model [article]

Prithu Banerjee, Wei Chen, Laks V.S. Lakshmanan
2018 arXiv   pre-print
In this setting, we study a novel problem of social welfare maximization: given item budgets, find an optimal allocation of items to seed nodes that maximizes the sum of expected utilities derived by users  ...  We provide the analysis of this result, which is highly nontrivial and along the way we give a solution to the prefix-preserving influence maximization problem, which could be of independent interest.  ...  It is easy to check that the classical influence maximization in the IC model, an NP hard problem, is a special case of WelMax. Function types.  ... 
arXiv:1807.02502v1 fatcat:yn5q4nkjm5fhjjhobsg3hx662a

Submodular Optimization Problems and Greedy Strategies: A Survey [article]

Yajing Liu, Edwin K. P. Chong, Ali Pezeshki, Zhenliang Zhang
2019 arXiv   pre-print
The greedy strategy is an approximation algorithm to solve optimization problems arising in decision making with multiple actions. How good is the greedy strategy compared to the optimal solution?  ...  In this survey, we mainly consider two classes of optimization problems where the objective function is submodular.  ...  These bounds are worst-case performance bounds, which means that the greedy strategy performs much better than those bounds in many cases.  ... 
arXiv:1905.03308v1 fatcat:xs444ca64rhl7magfhsdv4qqbm

Convex Optimization for Parallel Energy Minimization [article]

K. S. Sesh Kumar, Alvaro Barbero, Stefanie Jegelka, Francis Bach (LIENS,INRIA Paris - Rocquencourt)
2015 arXiv   pre-print
Energy minimization has been an intensely studied core problem in computer vision. With growing image sizes (2D and 3D), it is now highly desirable to run energy minimization algorithms in parallel.  ...  But many existing algorithms, in particular, some efficient combinatorial algorithms, are difficult to par-allelize.  ...  However, the decompositions used in the experiments here (Figure 1 ) only use a decomposition into 2-4 functions.  ... 
arXiv:1503.01563v1 fatcat:ge6qk5hvefcfpmk6jjvhka2m7a

Semimyopic Measurement Selection for Optimization Under Uncertainty

D. Tolpin, S. E. Shimony
2012 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
In particular, the efficiently computable method of "blinkered" VOI is proposed, and theoretical bounds for important special cases are examined.  ...  In this paper, the strict myopic assumption is relaxed into a scheme termed semi-myopic, providing a spectrum of methods that can improve the performance of measurement policies.  ...  Acknowledgments The research is partially supported by the IMG4 consortium under the MAGNET program, funded by the Israel Ministry of Trade and Industry, by the Israel Science Foundation, and by the Lynne  ... 
doi:10.1109/tsmcb.2011.2169247 pmid:22027390 fatcat:zpyzcu36szasvcdsiq6rm3iw5m

An Efficient Optimization Framework for Multi-Region Segmentation Based on Lagrangian Duality

Johannes Ulen, Petter Strandmark, Fredrik Kahl
2013 IEEE Transactions on Medical Imaging  
We apply our framework to the segmentation of the left and right ventricles, myocardium and the left ventricular papillary muscles in MRI and to lung segmentation in full-body X-ray CT.  ...  We efficiently optimize the model using a combination of graph cuts and Lagrangian duality which is faster and more memory efficient than current state of the art.  ...  Acknowledgments We thank the Cardiac MR group at the University Hospital of Lund for providing us with the Lund data set and expert delineations. We used Segment [19] to read the DICOM images.  ... 
doi:10.1109/tmi.2012.2218117 pmid:22987510 fatcat:qzkzbctgqfafnpdi3mce4u243i
« Previous Showing results 1 — 15 out of 20 results