├── LICENSE └── README.md /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2020 Recommendation Advertising & Search Community 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # papers 2 | 3 | # Unbiased LTR 4 | - [RecSys 19] [ PAL: a position-bias aware learning framework for CTR prediction in live recommender systems ](https://dl.acm.org/doi/pdf/10.1145/3298689.3347033) 5 | - [arxiv 18] [Modeling and Simultaneously Removing Bias via Adversarial Neural Networks](https://arxiv.org/pdf/1804.06909.pdf) 6 | - [arxiv 18] [A Study of Position Bias in Digital Library Recommender Systems](https://arxiv.org/abs/1802.06565) 7 | - [WSDM 17] [Unbiased Learning-to-Rank with Biased Feedback](https://arxiv.org/pdf/1608.04468.pdf) 8 | - [SIGIR 16] [Learning to Rank with Selection Bias in Personal Search](https://static.googleusercontent.com/media/research.google.com/zh-CN//pubs/archive/45286.pdf) 9 | 10 | # Multitask 11 | - [RecSys 19] [A Pareto-Eficient Algorithm for Multiple Objective Optimization in E-Commerce Recommendation](https://dl.acm.org/doi/pdf/10.1145/3298689.3346998) 12 | - [RecSys 19] [Recommending What Video to Watch Next: A Multitask Ranking System ](https://dl.acm.org/doi/pdf/10.1145/3298689.3346997) 13 | - [AAAI 19] [SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning](https://www.aaai.org/ojs/index.php/AAAI/article/view/3788/3666) 14 | - [arxiv 19] [Conversion Rate Prediction via Post-Click Behaviour Modeling](https://arxiv.org/pdf/1910.07099) 15 | - [arxiv 19] [Deep Bayesian Multi-Target Learning for Recommender Systems](https://arxiv.org/pdf/1902.09154.pdf) 16 | - [KDD 18] [Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts](https://dl.acm.org/doi/pdf/10.1145/3219819.3220007) 17 | - [SIGIR 18] [Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate](https://arxiv.org/pdf/1804.07931.pdf) 18 | 19 | 20 | --------------------------------------------------------------------------------