[RLAC]Representation Learning-Assisted Click-Through Rate Prediction[2019]_1647934875608.pdf
[Warm Up Cold-start Advertisements]Improving CTR Predictions via Learning to Learn ID Embeddings[2019]_1647934875708.pdf
[ALSH]Asymmetric LSH for Sublinear Time Maximum Inner Product Search[2014]_1647934875823.pdf
[BST]Behavior Sequence Transformer for E-commerce Recommendation in Alibaba[2019]_1647934875909.pdf
[DIEN] Deep Interest Evolution Network for Click-Through Rate Prediction (Alibaba 2019)_1647934876058.pdf
[DIN] Deep Interest Network for Click-Through Rate Prediction (Alibaba 2018)_1647934876301.pdf
[DSIN]Deep Session Interest Network for Click-Through Rate Predicti[2019]_1647934876659.pdf
[DSTN]Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction[2019]_1647934876941.pdf
[DTSF]Deep Time-Stream Framework for Click-Through Rate Prediction by Tracking Interest Evolution[2020]_1647934877055.pdf
[LSM]Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction[2019]_1647934877268.pdf
[MIMN]Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction[2019]_1647934877462.pdf
[NTM]Neural Turing Machines[2014]_1647934877610.pdf
[NTM]The_NTM_Introduction_And_Implementation[2017]_1647934877689.pdf
[REFORMER] THE EFFICIENT TRANSFORMER[2020]_1647934877745.pdf
[SIM]Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction[2020]_1647934877914.pdf
[Self-Attention]Attention is all you need(Google 2017)_1647934878110.pdf
[SeqFM]Sequence-Aware Factorization Machines(2019)_1647934878259.pdf
[AFM] Attentional Factorization Machines - Learning the Weight of Feature Interactions via Attention Networks (ZJU 2017)_1647934878421.pdf
[AutoInt] AutoInt Automatic Feature Interaction Learning via Self-Attentive Neural Networks(CIKM 2019)_1647934878601.pdf
[DCN] Deep & Cross Network for Ad Click Predictions (Stanford 2017)_1647934878683.pdf
[Deep Crossing] Deep Crossing - Web-Scale Modeling without Manually Crafted Combinatorial Features (Microsoft 2016)_1647934878766.pdf
[DeepFM] A Factorization-Machine based Neural Network for CTR Prediction (HIT-Huawei 2017)_1647934878836.pdf
[FFM] Field-aware Factorization Machines for CTR Prediction (Criteo 2016)_1647934878992.pdf
[FM] Fast Context-aware Recommendations with Factorization Machines (UKON 2011)_1647934879085.pdf
[FNN] Deep Learning over Multi-field Categorical Data (UCL 2016)_1647934879129.pdf
[LR] Predicting Clicks - Estimating the Click-Through Rate for New Ads (Microsoft 2007)_1647934879169.pdf
[NFM] Neural Factorization Machines for Sparse Predictive Analytics (NUS 2017)_1647934879303.pdf
[PNN] Product-based Neural Networks for User Response Prediction (SJTU 2016)_1647934879525.pdf
[Wide & Deep] Wide & Deep Learning for Recommender Systems (Google 2016)_1647934879568.pdf
[xDeepFM] xDeepFM - Combining Explicit and Implicit Feature Interactions for Recommender Systems (USTC 2018)_1647934879796.pdf
[ONN]Operation-aware Neural Networks for User Response Prediction[2019]_1647934875463.pdf
[PS-PLM] Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction (Alibaba 2017)_1647934875542.pdf
A Convolutional Click Prediction Model_1647934874095.pdf
[DSSM] Learning Deep Structured Semantic Models for Web Search using Clickthrough Data (UIUC 2013)_1647934874196.pdf
[ESMM] Entire Space Multi-Task Model - An Effective Approach for Estimating Post-Click Conversion Rate (Alibaba 2018)_1647934874251.pdf
[FAT-DeepFFM]Field Attentive Deep Field-aware Factorization Machine[2019]_1647934874289.pdf
[FGCNN]Feature Generation by Convolutional Neural Network forClick-Through Rate Predicti[2019]_1647934874321.pdf
[FLEN] Leveraging Field for Scalable CTR Predicti[2019]_1647934874508.pdf
[FTRL] Ad Click Prediction a View from the Trenches (Google 2013)_1647934874588.pdf
[Fi-GNN]Modeling Feature Interactions via Graph Neural Networks for CTR Prediction[2019]_1647934874672.pdf
[FiBiNET]Combining Feature Importance and Bilinear featureInteraction for Click-Through Rate Predict[2019]_1647934874768.pdf
[GBDT+LR] Practical Lessons from Predicting Clicks on Ads at Facebook (Facebook 2014)_1647934874913.pdf
[Image CTR] Image Matters - Visually modeling user behaviors using Advanced Model Server (Alibaba 2018)_1647934874989.pdf
[MINDN]Multi-Interest Network with Dynamic Routing for Recommendation at Tmall[2019]_1647934875077.pdf
[OENN]Order-aware Embedding Neural Network for CTR Predicti[2019]_1647934875207.pdf