LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation
Published in CIKM, 2024
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Publications
HierRec: Scenario-Aware Hierarchical Modeling for Multi-scenario Recommendations
Published in CIKM, 2024
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Diff-MSR: A Diffusion Model Enhanced Paradigm for Cold-Start Multi-Scenario Recommendation
Published in WSDM, 2024
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PLATE: A Prompt-Enhanced Paradigm for Multi-Scenario Recommendations
Published in SIGIR, 2023
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AutoDPQ: Automated Differentiable Product Quantization Embedding Compression Framework
Published in SIGIR, 2023
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Multi-Task Deep Recommender Systems: A Survey
Published in arxiv, 2023
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Exploration and Regularization of the Latent Action Space in Recommendation
Published in WWW, 2023
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Variational Reinforcement Learning for Hyper-Parameter Tuning of Adaptive Evolutionary Algorithm
Published in IEEE TETCI, 2022
Amortized Variational Deep Q Network
Published in Deep Reinforcement Learning Workshop at NeurIPS, 2020
We assumed action value function Q followed Cauchy or Gaussian distribution to encourage exploration and proposed Amortized Variational Deep Q Network with less parameters and less training time than Variational DQN and NoisyNet. 
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