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1 - 10 of 19
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Near optimal online algorithms and fast approximation algorithms for resource allocation problems Devanur N., Jain K., Sivan B., Wilkens C. Journal of the ACM 66(1): 1-41, 2019. Type: Article The resource allocation problem is an age-old problem with a rich history. This paper revisits the resource allocation problem, albeit in a different setting, finding “a middle ground between worst-case and stochastic [analyses]”: the ...
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Sep 21 2021 |
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A survey on deep neural network-based image captioning Liu X., Xu Q., Wang N. The Visual Computer 35(3): 445-470, 2019. Type: Article, Reviews: (2 of 2) Image captioning is an intriguing problem in the field of computer vision: given an input image, come up with suitable concise text that verbalizes that image well. This is currently a hot topic in the context of image understanding, and leverages...
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Jun 29 2020 |
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ELSA: a multilingual document summarization algorithm based on frequent itemsets and latent semantic analysis Cagliero L., Garza P., Baralis E. ACM Transactions on Information Systems 37(2): 1-33, 2019. Type: Article, Reviews: (1 of 2) Multi-document summarization involves the automatic generation of concise summaries of a number of textual documents, with the goal of succinctly presenting the most salient information. This allows readers to get the main idea without reading the...
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Jan 16 2020 |
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Characterizing and predicting individual traffic usage of mobile application in cellular network Wu J., Zeng M., Chen X., Li Y., Jin D. UbiComp 2018 (Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, Singapore, Oct 8-12, 2018) 852-861, 2018. Type: Proceedings The ubiquitous use of smart devices all over the world has contributed to an explosive increase in network traffic. Thus, methods for characterizing and predicting application-level traffic patterns from both individual and operator perspectives h...
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Jan 25 2019 |
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Making machine learning robust against adversarial inputs Goodfellow I., McDaniel P., Papernot N. Communications of the ACM 61(7): 56-66, 2018. Type: Article Machine learning (ML) has become ubiquitous in recent times. It is used in numerous (important) applications and its use will seemingly only increase. The current ML state of the art can be attributed to “nearly 50 years of research and deve...
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Oct 15 2018 |
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Instance-based object recognition in 3D point clouds using discriminative shape primitives Zhang J., Sun J. Machine Vision and Applications 29(2): 285-297, 2018. Type: Article The subject matter of this paper is 3D object recognition, particularly the detection of “objects of interest from cluttered 3D scenes” along with 3D poses of the objects. In fact, the authors study instance-based 3D object recognition...
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Jun 5 2018 |
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Toward optimal self-adjusting heaps Elmasry A. ACM Transactions on Algorithms 13(4): 1-14, 2017. Type: Article A self-adjusting heap is a heap data structure “that does not [need to] explicitly maintain structural information”; instead, during each access or update operation, the heap is adjusted in a uniform way. Why is a self-adjusting heap, ...
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Mar 19 2018 |
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Path-based methods on categorical structures for conceptual representation of Wikipedia articles Kucharczyk Ł., Szymański J. Journal of Intelligent Information Systems 48(2): 309-327, 2017. Type: Article The task of determining whether two documents cover similar topics pops up in many different contexts. This requires solving two different subtasks, namely, extraction of significant and useful characteristics/features from the document and applic...
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Nov 3 2017 |
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Graph isomorphism in quasipolynomial time [extended abstract] Babai L. STOC 2016 (Proceedings of the 48th Annual ACM SIGACT Symposium on the Theory of Computing, Cambridge, MA, Jun 19-21, 2016) 684-697, 2016. Type: Proceedings The graph isomorphism (GI) problem is an extremely interesting problem for computer scientists and mathematicians alike, and it is one of those problems whose complexity status is still unresolved. To this end, in this paper, Babai presents a brea...
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Jun 27 2017 |
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Support vector machines and perceptrons: learning, optimization, classification, and application to social networks Murty M., Raghava R., Springer International Publishing, New York, NY, 2016. 95 pp. Type: Book (978-3-319410-62-3) In the preface of the book, the authors boldly state: “SVMs [support vector machines] have revolutionized the research in the areas of machine learning and pattern recognition, specifically classification, so much that for a period of more t...
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Apr 11 2017 |
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