@@ -118,6 +118,7 @@ python -u tools/static_trainer.py -m models/rank/dnn/config.yaml # Training wit
118118 | Recall | [ NCF] ( models/recall/ncf/ ) <br >([ doc] ( https://paddlerec.readthedocs.io/en/latest/models/recall/ncf.html ) ) | [ Python CPU/GPU] ( https://aistudio.baidu.com/aistudio/projectdetail/3240152 ) | ✓ | ✓ | >=2.1.0 | [ WWW 2017] [ Neural Collaborative Filtering ] (https://arxiv.org/pdf/1708.05031.pdf) |
119119 | Recall | [ TiSAS] ( models/recall/tisas/ ) | - | ✓ | ✓ | >=2.1.0 | [ WSDM 2020] [ Time Interval Aware Self-Attention for Sequential Recommendation ] (https://cseweb.ucsd.edu/~jmcauley/pdfs/wsdm20b.pdf) |
120120 | Recall | [ ENSFM] ( models/recall/ensfm/ ) | - | ✓ | ✓ | >=2.1.0 | [ IW3C2 2020] [ Eicient Non-Sampling Factorization Machines for Optimal Context-Aware Recommendation ] (http://www.thuir.cn/group/~mzhang/publications/TheWebConf2020-Chenchong.pdf) |
121+ | Recall | [ MHCN] ( models/recall/mhcn/ ) | - | ✓ | ✓ | >=2.1.0 | [ WWW 2021] [ Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation ] (https://arxiv.org/pdf/2101.06448v3.pdf) |
121122 | Recall | [ GNN] ( https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/gnn/ ) | - | ✓ | ✓ | [ 1.8.5] ( https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5 ) | [ AAAI 2019] [ Session-based Recommendation with Graph Neural Networks ] (https://arxiv.org/abs/1811.00855) |
122123 | Recall | [ RALM] ( https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/look-alike_recall/ ) | - | ✓ | ✓ | [ 1.8.5] ( https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5 ) | [ KDD 2019] [ Real-time Attention Based Look-alike Model for Recommender System ] (https://arxiv.org/pdf/1906.05022.pdf) |
123124 | Rank | [ Logistic Regression] ( models/rank/logistic_regression/ ) <br >([ doc] ( https://paddlerec.readthedocs.io/en/latest/models/rank/logistic_regression.html ) ) | [ Python CPU/GPU] ( https://aistudio.baidu.com/aistudio/projectdetail/3240481 ) | ✓ | x | >=2.1.0 | / |
@@ -147,7 +148,7 @@ python -u tools/static_trainer.py -m models/rank/dnn/config.yaml # Training wit
147148 | Rank | [ Wide&Deep] ( models/rank/wide_deep/ ) <br >([ doc] ( https://paddlerec.readthedocs.io/en/latest/models/rank/wide_deep.html ) ) | [ Python CPU/GPU] ( https://aistudio.baidu.com/aistudio/projectdetail/3238421 ) | ✓ | x | >=2.1.0 | [ DLRS 2016] [ Wide & Deep Learning for Recommender Systems ] (https://dl.acm.org/doi/pdf/10.1145/2988450.2988454) |
148149 | Rank | [ FGCNN] ( https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/fgcnn/ ) | - | ✓ | ✓ | [ 1.8.5] ( https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5 ) | [ WWW 2019] [ Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction ] (https://arxiv.org/pdf/1904.04447.pdf) |
149150 | Rank | [ Fibinet] ( https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/fibinet/ ) | - | ✓ | ✓ | [ 1.8.5] ( https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5 ) | [ RecSys19] [ FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction ] ( https://arxiv.org/pdf/1905.09433.pdf) |
150- | Rank | [ Flen ] ( https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/ models/rank/flen/) | - | ✓ | ✓ | [ 1.8.5 ] ( https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5 ) | [ 2019] [ FLEN: Leveraging Field for Scalable CTR Prediction ] ( https://arxiv.org/pdf/1911.04690.pdf) |
151+ | Rank | [ FLEN ] ( models/rank/flen/ ) | - | ✓ | ✓ | >=2.1.0 | [ 2019] [ FLEN: Leveraging Field for Scalable CTR Prediction ] ( https://arxiv.org/pdf/1911.04690.pdf) |
151152 | Rank | [ DeepRec] ( models/rank/deeprec/ ) | - | ✓ | ✓ | >=2.1.0 | [ 2017] [ Training Deep AutoEncoders for Collaborative Filtering ] (https://arxiv.org/pdf/1708.01715v3.pdf) |
152153 | Rank | [ AutoFIS] ( models/rank/autofis/ ) | - | ✓ | ✓ | >=2.1.0 | [ KDD 2020] [ AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction ] (https://arxiv.org/pdf/2003.11235v3.pdf) |
153154 | Rank | [ DCN_V2] ( models/rank/dcn_v2/ ) | - | ✓ | ✓ | >=2.1.0 | [ WWW 2021] [ DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems ] (https://arxiv.org/pdf/2008.13535v2.pdf )
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