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Combating Product Review Spam Campaigns via Multiple Heterogeneous Pairwise Features., and . SDM, page 172-180. SIAM, (2015)Improving Sybil Detection via Graph Pruning and Regularization Techniques., , , and . ACML, volume 45 of JMLR Workshop and Conference Proceedings, page 189-204. JMLR.org, (2015)Mobile image based color correction using deblurring., , , , and . Computational Imaging, volume 9401 of SPIE Proceedings, page 940107. IS&T/SPIE, (2015)Environment rematching: Toward dependability improvement for self-adaptive applications., , , , and . ASE, page 592-597. IEEE, (2013)Optimistic Shared Memory Dependence Tracing (T)., , , , and . ASE, page 524-534. IEEE Computer Society, (2015)SGUARD: A Feature-Based Clustering Tool for Effective Spreadsheet Defect Detection., , , , , and . ASE, page 1142-1145. IEEE, (2019)GAIN: GPU-Based Constraint Checking for Context Consistency., , , , , , and . APSEC (1), page 319-326. IEEE Computer Society, (2014)Low Complexity Image Quality Measures for Dietary Assessment Using Mobile Devices., , , and . ISM, page 351-356. IEEE Computer Society, (2011)On Dropping Clusters to Regularize Graph Convolutional Neural Networks., , and . ECCV (21), volume 12366 of Lecture Notes in Computer Science, page 245-260. Springer, (2020)Convolutional neural networks for posed and spontaneous expression recognition., , , , and . ICME, page 769-774. IEEE Computer Society, (2017)