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07/04/2023
Cross-Element Combinatorial Selection for Multi-Element Creative in Display Advertising
The effectiveness of ad creatives is greatly influenced by their visual ...
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06/26/2023
A Collaborative Transfer Learning Framework for Cross-domain Recommendation
In the recommendation systems, there are multiple business domains to me...
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06/05/2023
Graph Based Long-Term And Short-Term Interest Model for Click-Through Rate Prediction
Click-through rate (CTR) prediction aims to predict the probability that...
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06/01/2023
Safe Offline Reinforcement Learning with Real-Time Budget Constraints
Aiming at promoting the safe real-world deployment of Reinforcement Lear...
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04/17/2023
MDDL: A Framework for Reinforcement Learning-based Position Allocation in Multi-Channel Feed
Nowadays, the mainstream approach in position allocation system is to ut...
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02/06/2023
PIER: Permutation-Level Interest-Based End-to-End Re-ranking Framework in E-commerce
Re-ranking draws increased attention on both academics and industries, w...
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02/01/2023
A Deep Behavior Path Matching Network for Click-Through Rate Prediction
User behaviors on an e-commerce app not only contain different kinds of ...
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05/20/2022
NMA: Neural Multi-slot Auctions with Externalities for Online Advertising
Online advertising driven by auctions brings billions of dollars in reve...
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04/02/2022
Hybrid Transfer in Deep Reinforcement Learning for Ads Allocation
Ads allocation, that allocates ads and organic items to limited slots in...
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04/02/2022
Learning List-wise Representation in Reinforcement Learning for Ads Allocation with Multiple Auxiliary Tasks
With the recent prevalence of reinforcement learning (RL), there have be...
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04/01/2022
Deep Page-Level Interest Network in Reinforcement Learning for Ads Allocation
A mixed list of ads and organic items is usually displayed in feed and h...
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09/09/2021
Cross DQN: Cross Deep Q Network for Ads Allocation in Feed
E-commerce platforms usually display a mixed list of ads and organic ite...
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12/22/2015
Recent Advances in Convolutional Neural Networks
In the last few years, deep learning has led to very good performance on...
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11/14/2015
Learning Fine-grained Features via a CNN Tree for Large-scale Classification
We propose a novel approach to enhance the discriminability of Convoluti...
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09/13/2015
Learning Contextual Dependencies with Convolutional Hierarchical Recurrent Neural Networks
Existing deep convolutional neural networks (CNNs) have shown their grea...
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05/18/2014