Fetching the paper…
Reading the bibliography…
In this article, we present a general approach to personalizing ads through encoding and learning from variable-length sequences of recent user actions and diverse representations.
EfficientNet: rethinking model scaling for convolutional neural networks
Mingxing Tan and Quoc V. Le. 2019 · 1905
Earlier work this paper cites.
Learning a unified embedding for visual search at Pinterest
Andrew Zhai, Hao-Yu Wu, Eric Tzeng, Dong Huk Park, and Charles Rosenberg. 2019 · 1908
Earlier work this paper cites.
Modeling task relationships in multi-task learning with multi-gate mixture-of-experts. In Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining . 1930–1939
Jiaqi Ma, Zhe Zhao, Xinyang Yi, Jilin Chen, Lichan Hong, and Ed H Chi. 2018b · 1939
Earlier work this paper cites.
Multitask learning
Rich Caruana. 1997 · 1997
Earlier work this paper cites.
Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
John Platt et al · 1999
Earlier work this paper cites.
Hierarchical probabilistic neural network language model. In International workshop on artificial intelligence and statistics . PMLR, 246–252
Frederic Morin and Yoshua Bengio. 2005 · 2005
Earlier work this paper cites.
Learning to rank: from pairwise approach to listwise approach. In Proceedings of the 24th international conference on Machine learning . 129–136
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, and Hang Li. 2007 · 2007
Earlier work this paper cites.
A scalable hierarchical distributed language model
Andriy Mnih and Geoffrey E Hinton. 2008 · 2008
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database. In 2009 IEEE conference on computer vision and pattern recognition . Ieee, 248–255
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. 2009 · 2009
Earlier work this paper cites.
Learning to rank for information retrieval
Tie-Yan Liu. 2011 · 2011
Earlier work this paper cites.
Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
TensorFlow: A system for large-scale machine learning. In 12th USENIX symposium on operating systems design and implementation (OSDI 16) . 265–283
Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, et al · 2016
Earlier work this paper cites.
Wide & deep learning for recommender systems. In Proceedings of the 1st workshop on deep learning for recommender systems . 7–10
Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, et al · 2016
Earlier work this paper cites.
Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter. 2016 · 2016
Earlier work this paper cites.
Deepintent: Learning attentions for online advertising with recurrent neural networks. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining . 1295–1304
Shuangfei Zhai, Keng-hao Chang, Ruofei Zhang, and Zhongfei Mark Zhang. 2016 · 2016
Earlier work this paper cites.
Enriching word vectors with subword information
Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017
Earlier work this paper cites.
On calibration of modern neural networks. In International conference on machine learning . PMLR, 1321–1330
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger. 2017 · 2017
Earlier work this paper cites.
An expectation maximization framework for Yule-Simon preferential attachment models
Lucas Roberts and Denisa Roberts. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Deep & cross network for ad click predictions
Ruoxi Wang, Bin Fu, Gang Fu, and Mingliang Wang. 2017 · 2017
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Cited alongside, same era.
Real-time personalization using embeddings for search ranking at Airbnb. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 311–320
Mihajlo Grbovic and Haibin Cheng. 2018 · 2018
Cited alongside, same era.
Self-attentive sequential recommendation. In 2018 IEEE international conference on data mining (ICDM) . IEEE, 197–206
Wang-Cheng Kang and Julian McAuley. 2018 · 2018
Cited alongside, same era.
Denisa AO Roberts and Lucas R Roberts. 2020 · 2020
Later among the works it cites.
Mixed negative sampling for learning two-tower neural networks in recommendations. In Companion Proceedings of the Web Conference 2020 . 441–447
Ji Yang, Xinyang Yi, Derek Zhiyuan Cheng, Lichan Hong, Yang Li, Simon Xiaoming Wang, Taibai Xu, and Ed H Chi. 2020 · 2020
Later among the works it cites.
Personalized graph neural networks with attention mechanism for session-aware recommendation
Mengqi Zhang, Shu Wu, Meng Gao, Xin Jiang, Ke Xu, and Liang Wang. 2020 · 2020
Later among the works it cites.
Comet.com home page
Comet.com. 2021 · 2021
Later among the works it cites.
Deep position-wise interaction network for CTR Prediction. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval . 1885–1889
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Andrew Zhai and Hao-Yu Wu. 2018 · 2018
Cited alongside, same era.
Learning item-interaction embeddings for user recommendations
Xiaoting Zhao, Raphael Louca, Diane Hu, and Liangjie Hong. 2018 · 2018
Cited alongside, same era.
Deep interest network for click-through rate prediction. In Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining . 1059–1068
Guorui Zhou, Xiaoqiang Zhu, Chenru Song, Ying Fan, Han Zhu, Xiao Ma, Yanghui Yan, Junqi Jin, Han Li, and Kun Gai. 2018 · 2018
Cited alongside, same era.
Behavior sequence transformer for e-commerce recommendation in Alibaba. In Proceedings of the 1st International Workshop on Deep Learning Practice for High-Dimensional Sparse Data . 1–4
Qiwei Chen, Huan Zhao, Wei Li, Pipei Huang, and Wenwu Ou. 2019 · 2019
Cited alongside, same era.
Practice on long sequential user behavior modeling for click-through rate prediction. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 2671–2679
Qi Pi, Weijie Bian, Guorui Zhou, Xiaoqiang Zhu, and Kun Gai. 2019 · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Cited alongside, same era.
Neural networks for Lorenz map prediction: A trip through time
Denisa Roberts. 2019 · 2019
Cited alongside, same era.
Autoint: Automatic feature interaction learning via self-attentive neural networks. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management . 1161–1170
Weiping Song, Chence Shi, Zhiping Xiao, Zhijian Duan, Yewen Xu, Ming Zhang, and Jian Tang. 2019 · 2019
Cited alongside, same era.
Jianqiang Huang, Ke Hu, Qingtao Tang, Mingjian Chen, Yi Qi, Jia Cheng, and Jun Lei. 2021 · 2021
Later among the works it cites.
Architecture and operation adaptive network for online recommendations. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining . 3139–3149
Lang Lang, Zhenlong Zhu, Xuanye Liu, Jianxin Zhao, Jixing Xu, and Minghui Shan. 2021 · 2021
Later among the works it cites.
DCN v2: Improved deep & cross network and practical lessons for web-scale learning to rank systems. In Proceedings of the Web Conference 2021 . 1785–1797
Ruoxi Wang, Rakesh Shivanna, Derek Cheng, Sagar Jain, Dong Lin, Lichan Hong, and Ed Chi. 2021 · 2021
Later among the works it cites.
Personalization in e-commerce product search by user-centric ranking
Lucia Yu, Ethan Benjamin, Congzhe Su, Yinlin Fu, Jon Eskreis-Winkler, Xiaoting Zhao, and Diane Hu. 2021 · 2021
Later among the works it cites.
Deep learning for click-through rate estimation
Weinan Zhang, Jiarui Qin, Wei Guo, Ruiming Tang, and Xiuqiang He. 2021a · 2021
Later among the works it cites.
How We Built A Context-Specific Bidding System for Etsy Ads
Alaa Awad, Congzhe Su, and Erica Greene. 2022 · 2022
Later among the works it cites.
ItemSage: Learning product embeddings for shopping recommendations at Pinterest
Paul Baltescu, Haoyu Chen, Nikil Pancha, Andrew Zhai, Jure Leskovec, and Charles Rosenberg. 2022 · 2022
Later among the works it cites.
Billion-scale pretraining with vision transformers for multi-task visual representations. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision . 564–573
Josh Beal, Hao-Yu Wu, Dong Huk Park, Andrew Zhai, and Dmitry Kislyuk. 2022 · 2022
Later among the works it cites.
PinnerFormer: Sequence modeling for user representation at Pinterest
Nikil Pancha, Andrew Zhai, Jure Leskovec, and Charles Rosenberg. 2022 · 2022
Later among the works it cites.
Sequence-graph duality: Unifying user modeling with self-attention for sequential recommendation
Zeren Shui, Ge Liu, Anoop Deoras, and George Karypis. 2022 · 2022
Later among the works it cites.
Rethinking personalized ranking at Pinterest: An end-to-end approach. In Proceedings of the 16th ACM Conference on Recommender Systems . 502–505
Jiajing Xu, Andrew Zhai, and Charles Rosenberg. 2022 · 2022
Later among the works it cites.
DHEN: A deep and hierarchical ensemble network for large-scale click-through rate prediction
Buyun Zhang, Liang Luo, Xi Liu, Jay Li, Zeliang Chen, Weilin Zhang, Xiaohan Wei, Yuchen Hao, Michael Tsang, Wenjun Wang, et al · 2022
Later among the works it cites.
Forecast 2023: Ad Spending Will Slow Down Next Year But Will Continue To Grow
2023 · 2023
Closest in time.
From Image Classification to Multitask Modeling: Building Etsy’s Search by Image Feature
Eden Dolev and Alaa Awad. 2023 · 2023
Closest in time.
Efficient Large-Scale Vision Representation Learning
Eden Dolev, Alaa Awad, Denisa Roberts, Zahra Ebrahimzadeh, Marcin Mejran, Vaibhav Malpani, and Mahir Yavuz. 2023 · 2023
Closest in time.