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GaP - a factor model for discrete data

GaP - a factor model for discrete data

최초 작성 2026-08-28마지막 수정 2026-10-23읽는 데 1분

노트 편집 ↗

EM algorithm, Gamma distribution, Poisson distribution

References

  • GaP - a factor model for discrete data

링크된 언급

1
Scalable Recommendation with Poisson Factorization

...and items. Related Work Poisson factorization 는 non-negative matrix factorization 에서 파생되었음 GaP - a factor model for discrete data Poisson Recommendation

함께 보면 좋은 글

Scalable Recommendation with Poisson Factorization

본 논문은 hierarchical Poisson matrix factorization(HPF) 모델을 제안.

Gamma distribution

The gamma distribution can be parameterized in terms of a shape parameter α = k and an inverse scale parameter β =1/θ, called a rate parameter. exponential distribution 에서는 rate...

EM algorithm

mixture gaussian problem, Probabilistic latent Semantic Indexing, K-means

Probabilistic Matrix Factorization

matrix factorization 은 다음과 같은 확률 모델로 바뀔 수 있다.

Poisson distribution

푸아송 분포는 확률론에서 단위 시간 안에 어떤 사건이 몇 번 발생할 것인지를 표현하는 이산 확률 분포이다.

Tutorial on Probablistic Latent Semantic Analysis

Tags Probabilistic latent Semantic Indexing, PLSI, multinomial distribution paper link https://arxiv.org/pdf/1212.3900.pdf notations size T: topic size, D: document size, N_d:...

Factorization Machines

combines the advantages of Support Vector Machines (SVM) with factorization models

Logistic Matrix Factorization for Implicit Feedback Data

Complex Embeddings for Simple Link Prediction

statistical relational learning 에서 link prediction 문제를 latent factorization 을 통해 푸는 방식을 제안한다.

Collaborative Filtering for Implicit Feedback Datasets

Alternating Least Squares