A repository of papers accompanying AICamp's machine learning paper club.
Whilst the COVID-19 quarantine lasts we will be conducting ML Paper Club remotely. Same day (), same time (18h00 London), but via webinar. Every week, we will post a link next to the paper so that you can join at the time of the Meetup. The link will be posted here a few minutes before the start of the discussion. Bear in mind that these meetings may be recorded for dissemination purposes.
During the discussion:
- Raise your (virtual) hand if you want to speak.
- Post in the Q&A section if you want something answered by the speaker.
- Feel free to make comments in the chat.
[04/08/2020] Link Christina presents: Hale, S. A., Fischer, P., & Brox, T. (2014, April). Global Connectivity and Multilinguals in the Twitter Network. In Proceedings of the SIGCHI Conference on Human Factors in Computing System (pp. 833–842). ACM, New York, NY, USA.
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Raghavan, U. N., Albert. R., & Kumara, S. (2007). Near linear time algorithm to detect community structures in large-scale networks. Physical Review. 76(3), (pp. 1-11).
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Hong, L., Convertino, G., & Chi, E. H. (2011). Language Matters in Twitter: A Large Scale Study. Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media, (pp. 518-521). Barcelona, Spain.
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Eleta, I., & Golbeck, J., Liu, R., & Yosinski, J. (2012). Bridging Languages in Social Networks: How Multilingual Users of Twitter Connect Language Communities? ASIST 2012, (pp. 1-4). Baltimore, MD, USA.
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Vedres., B. (2017) Forbidden triads and creative success in jazz: the Miles Davis factor. Applied Network Science 2(31), (pp. 2-25), Springer, USA.
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Graham, M. (2020) Regulate, replicate, and resist – the conjunctural geographies of platform urbanism, Urban Geography, Urban Geography, 41(3), (pp. 453-457) Taylor & Francis Group, UK.
For those new to machine learning, these are some recommended reading material:
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Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT press.
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Goldberg, Y. (2016). A primer on neural network models for natural language processing. Journal of Artificial Intelligence Research, 57, 345-420.
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Wu, Z., Pan, S., Chen, F., Long, G., Zhang, C., & Yu, P. S. (2019). A comprehensive survey on graph neural networks. arXiv preprint arXiv:1901.00596.
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Provost, F. and Fawcett, T. (2013). Data science for business. Sebastopol: O'Reilly.
We regularly record the presentations made during the Meetup (subject to the presenter's and attendees' approval). These videos are then uploaded to our YouTube channel so that those that can't attend are still able to profit from the presentations. If you's like to stay up to date with the presentations, just hit the subscribe button!
The papers that have been discussed in Paper Club meetings are.