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Factorization Machines 본문

AI/논문 리뷰

Factorization Machines

Orca0917 2023. 7. 25. 17:37

https://ieeexplore.ieee.org/document/5694074

 

Factorization Machines

In this paper, we introduce Factorization Machines (FM) which are a new model class that combines the advantages of Support Vector Machines (SVM) with factorization models. Like SVMs, FMs are a general predictor working with any real valued feature vector.

ieeexplore.ieee.org

 

 

이번에 살펴볼 논문은 sparse한 데이터를 사용해서도 평점 예측을 효과적으로 하고, 선형 시간내에 계산을 수행할 수 있는 Factorization Machine 모델이다. 추천시스템의 평점 예측이라는 특정 task에서만 적용가능한 모델이 아니며, regression, classification, ranking task에서도 적용가능한 general predictor이지만, 성능적인 측면에서는 task-specific한 모델과 유사하다는 것에 의미가 있다.

 

 

References

  1. S. Rendle, "Factorization Machines," 2010 IEEE International Conference on Data Mining, Sydney, NSW, Australia, 2010, pp. 995-1000, doi: 10.1109/ICDM.2010.127.
  2. Noble, William S. "What is a support vector machine?." Nature biotechnology 24.12 (2006): 1565-1567.
  3. Wikipedia contributors. (2023, July 5). Support vector machine. In Wikipedia, The Free Encyclopedia. Retrieved 08:48, July 25, 2023, from https://en.wikipedia.org/w/index.php?title=Support_vector_machine&oldid=1163600462
  4. ratsgo's blog. (2017, May 23). 서포트 벡터 머신 (Support Vector Machine). ratsgo’s blog. (n.d.). May 23, 2017, from  https://ratsgo.github.io/machine%20learning/2017/05/23/SVM/
  5. RISING FASTBALL, [추천시스템][paper review][구현] Factorization Machines, July 21, 2021, from https://supkoon.tistory.com/31

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