논문리뷰
1.[논문리뷰] Deep Neural Networks for YouTube Recommendations
대규모인 유튜브 환경에서 추천을 진행하기 위해 two stage information retrieval을 이용해 추천시스템을 구성하였다.이 과정에서 딥러닝을 적용하였고 성능이 dramatic하게 향상됐다.Two-stage information retrieval dich
2.[논문리뷰] Text Classification Improved by Integrating Bidirectional LSTM
arXiv:1611.06639 Text Classification Improved by Integrating Bidirectional LSTM with Two-dimensional Max Pooling 논문 리뷰입니다.RNN(Recurrent Neural Network
3.[논문리뷰] Attention-based LSTM for Aspect-level Sentiment Classification
Wang, Yequan, et al. "Attention-based LSTM for aspect-level sentiment classification." Proceedings of the 2016 conference on empirical methods in natu
4.[논문리뷰] Neural Collaborative Filtering
He, Xiangnan, et al. "Neural collaborative filtering." Proceedings of the 26th international conference on world wide web. 2017. 논문 리뷰입니다.최근 여러 분야에서의
5.[논문리뷰] Factorization Machines
Rendle, Steffen. "Factorization machines." 2010 IEEE International conference on data mining. IEEE, 2010. 논문 리뷰입니다. 0. Abstract Factorization Machin
6.[논문리뷰] Wide & Deep Learning for Recommender Systems
Cheng, Heng-Tze, et al. "Wide & deep learning for recommender systems." Proceedings of the 1st workshop on deep learning for recommender systems. 2016