Mixture-rank matrix approximation for collaborative filtering
Low-rank matrix approximation (LRMA) methods have achieved excellent accuracy among
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
Mixture-Rank Matrix Approximation for Collaborative Filtering
D Li, C Chen, W Liu, T Lu, N Gu… - Advances in Neural …, 2017 - proceedings.neurips.cc
Low-rank matrix approximation (LRMA) methods have achieved excellent accuracy among
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
[PDF][PDF] Mixture-Rank Matrix Approximation for Collaborative Filtering
D Li, C Chen, W Liu, T Lu, N Gu, SM Chu - researchgate.net
Low-rank matrix approximation (LRMA) methods have achieved excellent accuracy among
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
Mixture-rank matrix approximation for collaborative filtering
D Li, C Chen, W Liu, T Lu, N Gu… - Annual Conference on …, 2017 - research.ibm.com
Low-rank matrix approximation (LRMA) methods have achieved excellent accuracy among
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
Mixture-rank matrix approximation for collaborative filtering
D Li, C Chen, W Liu, T Lu, N Gu, SM Chu - Proceedings of the 31st …, 2017 - dl.acm.org
Low-rank matrix approximation (LRMA) methods have achieved excellent accuracy among
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
[PDF][PDF] Mixture-Rank Matrix Approximation for Collaborative Filtering
D Li, C Chen, W Liu, T Lu, N Gu, SM Chu - scholar.archive.org
Low-rank matrix approximation (LRMA) methods have achieved excellent accuracy among
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
[PDF][PDF] Mixture-Rank Matrix Approximation for Collaborative Filtering
D Li, C Chen, W Liu, T Lu, N Gu, SM Chu - papers.neurips.cc
Low-rank matrix approximation (LRMA) methods have achieved excellent accuracy among
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
[PDF][PDF] Mixture-Rank Matrix Approximation for Collaborative Filtering
D Li, C Chen, W Liu, T Lu, N Gu, SM Chu - recmind.cn
Low-rank matrix approximation (LRMA) methods have achieved excellent accuracy among
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …
today's collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item …