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08/11/2023
A Large Language Model Enhanced Conversational Recommender System
Conversational recommender systems (CRSs) aim to recommend high-quality ...
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06/06/2023
State Regularized Policy Optimization on Data with Dynamics Shift
In many real-world scenarios, Reinforcement Learning (RL) algorithms are...
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06/04/2023
Generative Flow Network for Listwise Recommendation
Personalized recommender systems fulfill the daily demands of customers ...
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02/07/2023
Multi-Task Recommendations with Reinforcement Learning
In recent years, Multi-task Learning (MTL) has yielded immense success i...
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02/07/2023
Disentangled Causal Embedding With Contrastive Learning For Recommender System
Recommender systems usually rely on observed user interaction data to bu...
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02/03/2023
Reinforcing User Retention in a Billion Scale Short Video Recommender System
Recently, short video platforms have achieved rapid user growth by recom...
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02/03/2023
Two-Stage Constrained Actor-Critic for Short Video Recommendation
The wide popularity of short videos on social media poses new opportunit...
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02/18/2021
Truncation-Free Matching System for Display Advertising at Alibaba
Matching module plays a critical role in display advertising systems. Wi...
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12/05/2020
Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising
In e-commerce advertising, the ad platform usually relies on auction mec...
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11/25/2020
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning
Modern online advertising systems inevitably rely on personalization met...
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11/11/2020
CAN: Revisiting Feature Co-Action for Click-Through Rate Prediction
Inspired by the success of deep learning, recent industrial Click-Throug...
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09/03/2020
Learning to Infer User Hidden States for Online Sequential Advertising
To drive purchase in online advertising, it is of the advertiser's great...
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08/20/2020
A Deep Prediction Network for Understanding Advertiser Intent and Satisfaction
For e-commerce platforms such as Taobao and Amazon, advertisers play an ...
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07/31/2020
COLD: Towards the Next Generation of Pre-Ranking System
Multi-stage cascade architecture exists widely in many industrial system...
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06/29/2020
Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising
In E-commerce, advertising is essential for merchants to reach their tar...
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06/27/2020
Learning Optimal Tree Models Under Beam Search
Retrieving relevant targets from an extremely large target set under com...
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06/17/2020
DCAF: A Dynamic Computation Allocation Framework for Online Serving System
Modern large-scale systems such as recommender system and online adverti...
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06/10/2020
Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction
Rich user behavior data has been proven to be of great value for click-t...
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05/09/2020
Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising
Bipartite b-matching is fundamental in algorithm design, and has been wi...
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11/14/2019
Progressive Feature Polishing Network for Salient Object Detection
Feature matters for salient object detection. Existing methods mainly fo...
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08/19/2019
Learning to Advertise for Organic Traffic Maximization in E-Commerce Product Feeds
Most e-commerce product feeds provide blended results of advertised prod...
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06/25/2019
Res-embedding for Deep Learning Based Click-Through Rate Prediction Modeling
Recently, click-through rate (CTR) prediction models have evolved from s...
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05/24/2019
Bid Optimization by Multivariable Control in Display Advertising
Real-Time Bidding (RTB) is an important paradigm in display advertising,...
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05/22/2019
Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction
Click-through rate (CTR) prediction is critical for industrial applicati...
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05/02/2019
Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction
User response prediction, which models the user preference w.r.t. the pr...
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03/26/2019
Improve Diverse Text Generation by Self Labeling Conditional Variational Auto Encoder
Diversity plays a vital role in many text generating applications. In re...
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02/19/2019
Joint Optimization of Tree-based Index and Deep Model for Recommender Systems
Large-scale industrial recommender systems are usually confronted with c...
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09/11/2018
Deep Interest Evolution Network for Click-Through Rate Prediction
Click-through rate (CTR) prediction, whose goal is to estimate the proba...
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09/10/2018
A Multi-Agent Reinforcement Learning Method for Impression Allocation in Online Display Advertising
In online display advertising, guaranteed contracts and real-time biddin...
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09/10/2018
Learning to Advertise with Adaptive Exposure via Constrained Two-Level Reinforcement Learning
For online advertising in e-commerce, the traditional problem is to assi...
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09/05/2018
Semantic Human Matting
Human matting, high quality extraction of humans from natural images, is...
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04/21/2018
Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate
Estimating post-click conversion rate (CVR) accurately is crucial for ra...
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02/27/2018
Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising
Real-time advertising allows advertisers to bid for each impression for ...
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02/23/2018
Budget Constrained Bidding by Model-free Reinforcement Learning in Display Advertising
Real-time bidding (RTB) is almost the most important mechanism in online...
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01/08/2018
Learning Tree-based Deep Model for Recommender Systems
We propose a novel recommendation method based on tree. With user behavi...
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11/17/2017
Image Matters: Jointly Train Advertising CTR Model with Image Representation of Ad and User Behavior
Click Through Rate(CTR) prediction is vital for online advertising syste...
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08/14/2017
Rocket Launching: A Universal and Efficient Framework for Training Well-performing Light Net
Models applied on real time response task, like click-through rate (CTR)...
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06/21/2017
Deep Interest Network for Click-Through Rate Prediction
To better extract users' interest by exploiting the rich historical beha...
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04/18/2017
Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction
CTR prediction in real-world business is a difficult machine learning pr...
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02/27/2017
Optimized Cost per Click in Taobao Display Advertising
Taobao, as the largest online retail platform in the world, provides bil...
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11/19/2012