Deep & Cross Network for Ad Click Predictions

17 August 2017

Papers citing "Deep & Cross Network for Ad Click Predictions"

50 / 164 papers shown

Title
AdaEnsemble: Learning Adaptively Sparse Structured Ensemble Network for Click-Through Rate Prediction Yachen Yan Liubo Li 22 3 0 06 Jan 2023
xDeepInt: a hybrid architecture for modeling the vector-wise and bit-wise feature interactions Yachen Yan Liubo Li 32 9 0 03 Jan 2023
Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction Shiwei Li Huifeng Guo Luyao Hou Wei Zhang Xing Tang Ruiming Tang Rui Zhang Rui Li MQ 162 9 0 12 Dec 2022
CL4CTR: A Contrastive Learning Framework for CTR Prediction Fang Wang Yingxu Wang Dongsheng Li Hansu Gu Tun Lu Peng Zhang Ning Gu SSL 22 42 0 01 Dec 2022
T2G-Former: Organizing Tabular Features into Relation Graphs Promotes Heterogeneous Feature Interaction Jiahuan Yan Jintai Chen YiXuan Wu Danny Chen Jian Wu 37 36 0 30 Nov 2022
Merlin HugeCTR: GPU-accelerated Recommender System Training and Inference Zehuan Wang Yingcan Wei Minseok Lee Matthias Langer F. Yu ... Daniel G. Abel Xu Guo Jianbing Dong Ji Shi Kunlun Li GNN LRM 25 32 0 17 Oct 2022
SML:Enhance the Network Smoothness with Skip Meta Logit for CTR Prediction Wenlong Deng Lang Lang Ziqiang Liu B. Liu 26 0 0 09 Oct 2022
Higher-order Neural Additive Models: An Interpretable Machine Learning Model with Feature Interactions Minkyu Kim Hyunjin Choi Jinho Kim FAtt 38 8 0 30 Sep 2022
Efficient Long Sequential User Data Modeling for Click-Through Rate Prediction Qiwei Chen Yue Xu Changhua Pei Shanshan Lv Tao Zhuang Junfeng Ge 3DV 23 3 0 25 Sep 2022
Billion-user Customer Lifetime Value Prediction: An Industrial-scale Solution from Kuaishou Kunpeng Li Guangcui Shao Naijun Yang Xiao Fang Yang Song 26 14 0 29 Aug 2022
Can you recommend content to creatives instead of final consumers? A RecSys based on user's preferred visual styles Raul Gomez Bruballa Lauren Burnham-King Alessandra Sala 25 0 0 23 Aug 2022
JDRec: Practical Actor-Critic Framework for Online Combinatorial Recommender System Xin Zhao Zhiwei Fang Yuchen Guo Jie He Wenlong Chen Changping Peng 26 0 0 27 Jul 2022
$The trade-offs of model size in large recommendation models : A 10000 $\times$ compressed criteo-tb DLRM model (100 GB parameters to mere 10MB)$ The trade-offs of model size in large recommendation models : A 10000 $\times$ compressed criteo-tb DLRM model (100 GB parameters to mere 10MB) Aditya Desai Anshumali Shrivastava AI4CE 20 3 0 21 Jul 2022
Revisiting Pretraining Objectives for Tabular Deep Learning Ivan Rubachev Artem Alekberov Yu. V. Gorishniy Artem Babenko LMTD 21 41 0 07 Jul 2022
Transfer Learning with Deep Tabular Models Roman Levin Valeriia Cherepanova Avi Schwarzschild Arpit Bansal C. Bayan Bruss Tom Goldstein A. Wilson Micah Goldblum OOD FedML LMTD 75 58 0 30 Jun 2022
Cooperative Retriever and Ranker in Deep Recommenders Xunpeng Huang Defu Lian Jin Chen Liu Zheng Xing Xie Enhong Chen VLM AI4TS 30 11 0 28 Jun 2022
PHN: Parallel heterogeneous network with soft gating for CTR prediction Ri-Qi Su Alphonse Houssou Hounye Cong Cao Muzhou Hou 23 1 0 18 Jun 2022
Boosting Factorization Machines via Saliency-Guided Mixup Chenwang Wu Defu Lian Yong Ge Min Zhou Enhong Chen Dacheng Tao 19 4 0 17 Jun 2022
FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning Meisam Hejazinia Dzmitry Huba Ilias Leontiadis Kiwan Maeng Mani Malek Luca Melis Ilya Mironov Milad Nasr Kaikai Wang Carole-Jean Wu FedML 21 5 0 07 Jun 2022
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity Kiwan Maeng Haiyu Lu Luca Melis John Nguyen Michael G. Rabbat Carole-Jean Wu FedML 51 31 0 30 May 2022
Sampling Is All You Need on Modeling Long-Term User Behaviors for CTR Prediction Yue Cao Xiaojiang Zhou Jiaqi Feng Peihao Huang Yao Xiao Dayao Chen Sheng Chen 82 40 0 20 May 2022
TransTab: Learning Transferable Tabular Transformers Across Tables Zifeng Wang Jimeng Sun LMTD 46 137 0 19 May 2022
Hybrid CNN Based Attention with Category Prior for User Image Behavior Modeling Xin Chen Qingtao Tang Ke Hu Yue Xu Shi Qiu Jia Cheng Jun Lei 27 5 0 05 May 2022
CowClip: Reducing CTR Prediction Model Training Time from 12 hours to 10 minutes on 1 GPU Zangwei Zheng Peng Xu Xuan Zou Da Tang Zhen Li ... Xiangzhuo Ding Fuzhao Xue Ziheng Qing Youlong Cheng Yang You VLM 49 7 0 13 Apr 2022
PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems Yuanxing Zhang Langshi Chen Siran Yang Man Yuan Hui-juan Yi ... Yong Li Dingyang Zhang Wei Lin Lin Qu Bo Zheng 43 32 0 11 Apr 2022
A Comprehensive Survey on Automated Machine Learning for Recommendations Bo Chen Xiangyu Zhao Yejing Wang Wenqi Fan Huifeng Guo Ruiming Tang AI4TS 31 6 0 04 Apr 2022
CTAB-GAN+: Enhancing Tabular Data Synthesis Zilong Zhao A. Kunar Robert Birke L. Chen 35 78 0 01 Apr 2022
APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction Bencheng Yan Pengjie Wang Kai Zhang Feng Li Hongbo Deng Jian Xu Bo Zheng 27 20 0 30 Mar 2022
DHEN: A Deep and Hierarchical Ensemble Network for Large-Scale Click-Through Rate Prediction Buyun Zhang Liangchen Luo Xi Liu Jay Li Zeliang Chen ... Yasmine Badr Jongsoo Park Jiyan Yang Dheevatsa Mudigere Ellie Wen 3DV 22 11 0 11 Mar 2022
On Embeddings for Numerical Features in Tabular Deep Learning Yura Gorishniy Ivan Rubachev Artem Babenko LMTD 21 157 0 10 Mar 2022
MetaCon: Unified Predictive Segments System with Trillion Concept Meta-Learning Keqian Li Yifan Hu Logan Palanisamy Lisa Jones A. Gupta J. E. Grigsby Ili Selinger Matt Gillingham Fei Tan 28 1 0 09 Mar 2022
SuperCone: Unified User Segmentation over Heterogeneous Experts via Concept Meta-learning Keqian Li Yifan Hu 38 0 0 09 Mar 2022
BagPipe: Accelerating Deep Recommendation Model Training Saurabh Agarwal Chengpo Yan Ziyi Zhang Shivaram Venkataraman 37 18 0 24 Feb 2022
Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer Erxue Min Yu Rong Tingyang Xu Yatao Bian P. Zhao Junzhou Huang Da Luo Kangyi Lin Sophia Ananiadou 39 33 0 25 Jan 2022
An integrated recurrent neural network and regression model with spatial and climatic couplings for vector-borne disease dynamics Zhijian Li Jack Xin Guofa Zhou 27 0 0 23 Jan 2022
Building a Performance Model for Deep Learning Recommendation Model Training on GPUs Zhongyi Lin Louis Feng E. K. Ardestani Jaewon Lee J. Lundell Changkyu Kim A. Kejariwal John Douglas Owens 30 19 0 19 Jan 2022
Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework Xiaoxiao Xu Chen Yang Qian Yu Zhiwei Fang Jiaxing Wang Chaosheng Fan Yang He Changping Peng Zhangang Lin Jingping Shao CML 28 27 0 17 Jan 2022
RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems Zohreh Ovaisi Shelby Heinecke Jia Li Yongfeng Zhang Elena Zheleva Caiming Xiong 33 21 0 12 Jan 2022
Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection Yongchun Zhu Dongbo Xi Bowen Song Fuzhen Zhuang Shuai Chen Xi Gu Qing He 24 59 0 04 Jan 2022
HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework Xupeng Miao Hailin Zhang Yining Shi Xiaonan Nie Zhi-Xin Yang Yangyu Tao Bin Cui 24 57 0 14 Dec 2021
Enhanced Exploration in Neural Feature Selection for Deep Click-Through Rate Prediction Models via Ensemble of Gating Layers L. Guan Xia Xiao Ming-yue Chen Youlong Cheng 27 1 0 07 Dec 2021
Differentiable NAS Framework and Application to Ads CTR Prediction Ravi Krishna Aravind Kalaiah Bichen Wu Maxim Naumov Dheevatsa Mudigere M. Smelyanskiy Kurt Keutzer 28 8 0 25 Oct 2021
A Real-Time Energy and Cost Efficient Vehicle Route Assignment Neural Recommender System A. Moawad Zhijian Li Ines Pancorbo K. M. Gurumurthy Vincent Freyermuth E. Islam R. Vijayagopal M. Stinson A. Rousseau 22 8 0 21 Oct 2021
AEFE: Automatic Embedded Feature Engineering for Categorical Features Zhenyuan Zhong Jie Yang Yacong Ma Shoubin Dong Jinlong Hu 28 2 0 19 Oct 2021
Modeling Dynamic Attributes for Next Basket Recommendation Yong-Guang Chen Jia Li Chenghao Liu Chenxi Li M. Anderle Julian McAuley Caiming Xiong 38 18 0 23 Sep 2021
Secure Your Ride: Real-time Matching Success Rate Prediction for Passenger-Driver Pairs Yuandong Wang Hongzhi Yin Lian Wu Tong Chen Chunyang Liu 29 7 0 14 Sep 2021
Top-N Recommendation with Counterfactual User Preference Simulation Mengyue Yang Quanyu Dai Zhenhua Dong Xu Chen Xiuqiang He Jun Wang CML BDL 50 65 0 02 Sep 2021
Learning Effective and Efficient Embedding via an Adaptively-Masked Twins-based Layer Bencheng Yan Pengjie Wang Kai Zhang Wei Lin Kuang-chih Lee Jian Xu Bo Zheng 29 26 0 24 Aug 2021
Simple Modifications to Improve Tabular Neural Networks J. Fiedler LMTD 91 19 0 06 Aug 2021
$Random Offset Block Embedding Array (ROBE) for CriteoTB Benchmark MLPerf DLRM Model : 1000$\times$ Compression and 3.1$\times$ Faster Inference$ Random Offset Block Embedding Array (ROBE) for CriteoTB Benchmark MLPerf DLRM Model : 1000 $\times$ Compression and 3.1 $\times$ Faster Inference Aditya Desai Li Chou Anshumali Shrivastava AI4CE 25 6 0 04 Aug 2021