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.QUESTION

Information system

Description

Find 10 academic sources (Journals, Academic Publications, Industry Sources, Trade Magazines, News Articles. Not: Wikipedia, Course Cheat Sites, the textbook). Each source needs an appropriately cited APA reference and a quick summary of why the source is interesting. Do not include any direct quotes.

Topic
Everyone consumes media, and that media reflects the world around us. Frequently, the themes of Information Systems can be found in a number of works for entertainment. Select a show from Netflix or some other online streaming service. If you don’t have access to any online streaming services, you can select a book or a series of books. Relate how the show can be summarized using one of the three main models from the text: Seesaw Model, Distillation Model, or Decision Mode Ternary.

Subject	Computer Technology	Pages	8	Style	APA

Answer

- 1. 1. Anil, R., Pereyra, G., Passos, A., Ormandi, R., Dahl, G. E., & Hinton, G. E. (2018). Large scale distributed neural network training through online distillation. arXiv preprint arXiv:1804.03235.
      
      This is an interesting reference in that the information it provides has a direct bearing to the topic under discussion.
      
      Chen, G., Choi, W., Yu, X., Han, T., & Chandraker, M. (2017). Learning efficient object detection models with knowledge distillation. In Advances in Neural Information Processing Systems (pp. 742-751).
      
      This reference is an illustration of how data in the larger model in the distillation model is converted for comprehension by the smaller model.
      
      Freitag, M., Al-Onaizan, Y., & Sankaran, B. (2017). Ensemble distillation for neural machine translation. arXiv preprint arXiv:1702.01802.
      
      This reference reveals information about the larger model in the distillation model.
      
      Fukuda, T., Suzuki, M., Kurata, G., Thomas, S., Cui, J., & Ramabhadran, B. (2017, August). Efficient Knowledge Distillation from an Ensemble of Teachers. In Interspeech (pp. 3697-3701).
      
      This particular reference greatly enlightens on the knowledge conversion procedure within the distillation model as a whole.
      
      Khazraee, S. M., Jahanmiri, A. H., & Ghorayshi, S. A. (2011). Model reduction and optimization of reactive batch distillation based on the adaptive neuro-fuzzy inference system and differential evolution. Neural Computing and Applications, 20(2), 239-248.
      
      Park, W., Kim, D., Lu, Y., & Cho, M. (2019). Relational knowledge distillation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 3967-3976).
      
      Radosavovic, I., Dollár, P., Girshick, R., Gkioxari, G., & He, K. (2018). Data distillation: Towards omni-supervised learning. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 4119-4128).
      
      Tang, J., & Wang, K. (2018, July). Ranking distillation: Learning compact ranking models with high performance for recommender system. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 2289-2298).
      
      Wang, J., Bao, W., Sun, L., Zhu, X., Cao, B., & Philip, S. Y. (2019, July). Private model compression via knowledge distillation. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, pp. 1190-1197).
      
      Yang, Z., Shou, L., Gong, M., Lin, W., & Jiang, D. (2019). Model compression with multi-task knowledge distillation for web-scale question answering system. arXiv preprint arXiv:1904.09636.
      
      Yang, Z., Shou, L., Gong, M., Lin, W., & Jiang, D. (2020, January). Model compression with two-stage multi-teacher knowledge distillation for web question answering system. In Proceedings of the 13th International Conference on Web Search and Data Mining (pp. 690-698).
      
      The latter six references all promote a similar agenda on the essay; they highlight the procedures involved in the collection and conversion of information within the distillation model and the associated processes.