Workshop to create a sensor application over a WiFi Mesh network - GitHub - binnes/WiFiMeshRaspberryPi: Workshop to create a sensor application over a WiFi Mesh network
Engineer friends often ask me: Graph Deep Learning sounds great, but are there any big commercial success stories? Is it being deployed in practical applications? Besides the obvious ones–recommendation systems at Pinterest, Alibaba and Twitter–a slightly nuanced success story is the Transformer architecture, which has taken the NLP industry by storm. Through this post, I want to establish links between Graph Neural Networks (GNNs) and Transformers. I’ll talk about the intuitions behind model architectures in the NLP and GNN communities, make connections using equations and figures, and discuss how we could work together to drive progress.
J. Zhang, Y. Dong, Y. Wang, J. Tang, and M. Ding. Proceedings of the 28th International Joint Conference on Artificial Intelligence, page 4278–4284. AAAI Press, (Aug 10, 2019)
Z. Yang, D. Yang, C. Dyer, X. He, A. Smola, and E. Hovy. Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, page 1480--1489. San Diego, California, Association for Computational Linguistics, (June 2016)
Y. Kim, K. Stratos, and D. Kim. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), page 643--653. Vancouver, Canada, Association for Computational Linguistics, (July 2017)
J. Lin, R. Nogueira, and A. Yates. (2020)cite arxiv:2010.06467Comment: Final preproduction version of volume in Synthesis Lectures on Human Language Technologies by Morgan & Claypool.
Q. Le, and T. Mikolov. Proceedings of the 31st International Conference on Machine Learning, volume 32 of Proceedings of Machine Learning Research, page 1188--1196. Bejing, China, PMLR, (June 2014)
S. Wang, L. Hu, Y. Wang, X. He, Q. Sheng, M. Orgun, L. Cao, F. Ricci, and P. Yu. (2021)cite arxiv:2105.06339Comment: Accepted by IJCAI 2021 Survey Track, copyright is owned to IJCAI. The first systematic survey on graph learning based recommender systems. arXiv admin note: text overlap with arXiv:2004.11718.
M. Paris, and R. Jäschke. Proceedings of the 14th International Conference on Knowledge Science, Engineering and Management, volume 12816 of Lecture Notes in Artificial Intelligence, page 1--14. Springer, (2021)
M. Dacrema, P. Cremonesi, and D. Jannach. (2019)cite arxiv:1907.06902Comment: Source code available at: https://github.com/MaurizioFD/RecSys2019_DeepLearning_Evaluation.
P. Xia, S. Wu, and B. Van Durme. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), page 7516--7533. Association for Computational Linguistics, (November 2020)
J. Schlötterer, C. Seifert, and M. Granitzer. Machine Learning and Knowledge Extraction, page 237--251. Cham, Springer International Publishing, (2017)
R. Schwarzenberg, L. Raithel, and D. Harbecke. (2019)cite arxiv:1904.01500Comment: NAACL-HLT 2019 Workshop on Evaluating Vector Space Representations for NLP (RepEval).
D. Gibson, J. Kleinberg, and P. Raghavan. Proceedings of the ninth ACM conference on Hypertext and hypermedia : links, objects, time and space---structure in hypermedia systems links, objects, time and space---structure in hypermedia systems - HYPERTEXT \textquotesingle98, ACM Press, (1998)
G. Flake, S. Lawrence, and C. Giles. Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining - KDD \textquotesingle00, ACM Press, (2000)
D. Liben-Nowell, and J. Kleinberg. Proceedings of the twelfth international conference on Information and knowledge management - CIKM \textquotesingle03, ACM Press, (2003)
M. Potamias, F. Bonchi, C. Castillo, and A. Gionis. Proceeding of the 18th ACM conference on Information and knowledge management - CIKM \textquotesingle09, ACM Press, (2009)
C. Scholz, M. Atzmueller, M. Kibanov, and G. Stumme. Proceedings of the 2013 ACM/IEEE International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013, Niagara Falls, Canada, August 25-28, 2013, page 356--363. New York, NY, USA, ACM, (2013)
A. Schmidt, and G. Stumme. Proceedings of the 21th International Conference on Knowledge Engineering and Knowledge Management (EKAW), page 370-385. Springer, (2018)
M. Atzmueller, L. Thiele, G. Stumme, and S. Kauffeld. Proc. Annual Machine Learning Conference of the Benelux (Benelearn 2017), Eindhoven, The Netherlands, Eindhoven University of Technology, (2017)
M. Atzmueller, L. Thiele, G. Stumme, and S. Kauffeld. Proc. ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication, New York, NY, USA, ACM Press, (2016)
P. Singer, D. Helic, A. Hotho, and M. Strohmaier. Proceedings of the 24th International Conference on World Wide Web, page 1003--1013. Republic and Canton of Geneva, Switzerland, International World Wide Web Conferences Steering Committee, (2015)
S. Myers, A. Sharma, P. Gupta, and J. Lin. 23rd International World Wide Web Conference, WWW '14, Seoul, Republic of Korea, April 7-11, 2014, Companion Volume, page 493--498. (2014)
J. Huang, Z. Zhuang, J. Li, and C. Giles. Proceedings of the 2008 International Conference on Web Search and Data Mining, page 107--116. New York, NY, USA, ACM, (2008)
F. Otto, M. Ring, D. Landes, and A. Hotho. ECCWS2016-Proceedings fo the 15th European Conference on Cyber Warfare and Security, page 437. Academic Conferences and publishing limited, (2016)