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09/06/2023
Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning
We study the budget allocation problem in online marketing campaigns tha...
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08/31/2023
AntM^2C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction
Click-through rate (CTR) prediction is a crucial issue in recommendation...
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08/25/2023
Model-free Reinforcement Learning with Stochastic Reward Stabilization for Recommender Systems
Model-free RL-based recommender systems have recently received increasin...
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08/21/2023
Leveraging Large Language Models for Pre-trained Recommender Systems
Recent advancements in recommendation systems have shifted towards more ...
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08/21/2023
Enhancing Recommender Systems with Large Language Model Reasoning Graphs
Recommendation systems aim to provide users with relevant suggestions, b...
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05/30/2023
Who Would be Interested in Services? An Entity Graph Learning System for User Targeting
With the growing popularity of various mobile devices, user targeting ha...
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12/28/2021
Adversarial Learning for Incentive Optimization in Mobile Payment Marketing
Many payment platforms hold large-scale marketing campaigns, which alloc...
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08/29/2021
A Policy Efficient Reduction Approach to Convex Constrained Deep Reinforcement Learning
Although well-established in general reinforcement learning (RL), value-...
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08/27/2021
A framework for massive scale personalized promotion
Technology companies building consumer-facing platforms may have access ...
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07/30/2021
Adaptive Optimizers with Sparse Group Lasso for Neural Networks in CTR Prediction
We develop a novel framework that adds the regularizers of the sparse gr...
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05/25/2021
Graph Neural Network Based VC Investment Success Prediction
Predicting the start-ups that will eventually succeed is essentially imp...
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02/03/2021
LinkLouvain: Link-Aware A/B Testing and Its Application on Online Marketing Campaign
A lot of online marketing campaigns aim to promote user interaction. The...
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02/27/2020
