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Sequential Recommendation (SR) plays a pivotal role in recommender systems by tailoring recommendations to user preferences based on their non-stationary historical interactions.
“Stochastic analysis on manifolds”
Elton Hsu · 2002
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“Factorizing personalized Markov chains for next-basket recommendation”
Steffen Rendle, Christoph Freudenthaler and Lars Schmidt-Thieme · 2010
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“On Using Very Large Target Vocabulary for Neural Machine Translation”
Sébastien Jean, Kyunghyun Cho, Roland Memisevic and Yoshua Bengio · 2014
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“Session-based recommendations with recurrent neural networks”
Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas and Domonkos Tikk · 2015
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“Variational dropout and the local reparameterization trick”
DiederikP. Kingma, Tim Salimans and Max Welling · 2015
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“Deep Variational Information Bottleneck”
AlexanderA. Alemi, Ian Fischer, JoshuaV. Dillon and Kevin Murphy · 2016
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“Fusing Similarity Models with Markov Chains for Sparse Sequential Recommendation”, 2016
He Ruining and McAuley Julian · 2016
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“Dynamic Routing Between Capsules”
Sara Sabour, Nicholas Frosst and GeoffreyE. Hinton · 2017
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“Attention is All you Need”
Ashish Vaswani et al · 2017
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“Self-Attentive Sequential Recommendation”
Wang-Cheng Kang and Julian McAuley · 2018
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“Variational autoencoders for collaborative filtering”
Dawen Liang, Rahul Krishnan, Matthew Hoffman and Tony Jebara · 2018
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“Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding”
Jiaxi Tang and Ke Wang · 2018
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“BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding”
Jacob Devlin, Ming-Wei Chang, Kenton Lee and Kristina Toutanova · 2019
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“Multi-Interest Network with Dynamic Routing for Recommendation at Tmall”
Chao Li et al · 2019
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“BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer”
Fei Sun et al · 2019
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“Controllable Multi-Interest Framework for Recommendation”
Yukuo Cen et al · 2020
“Adversarial and Contrastive Variational Autoencoder for Sequential Recommendation”
Zhe Xie et al · 2021
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“Variational Self-attention Network for Sequential Recommendation”
Jing Zhao et al · 2021
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“Riemannian score-based generative modelling”
Valentin De et al · 2022
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“Sequential Recommendation with Diffusion Models”, 2023
Hanwen Du et al · 2023
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“DiffuRec: A Diffusion Model for Sequential Recommendation”, 2023
Zihao Li, Aixin Sun and Chenliang Li · 2023
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“Diffusion Recommender Model”, 2023
Wenjie Wang et al · 2023
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“Denoising Diffusion Probabilistic Models.”
Jonathan Ho, Ajay Jain and Pieter Abbeel · 2020
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Ruiyang Ren et al · 2020
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Prafulla Dhariwal and Alex Nichol · 2021
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Zhengyi Yang et al · 2023
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“Deconstructing Denoising Diffusion Models for Self-Supervised Learning”
Xinlei Chen, Zhuang Liu, Saining Xie and Kaiming He · 2024
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“Discrete conditional diffusion for reranking in recommendation”
Xiao Lin et al · 2024
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