huangsg1 / Tree-Based-Feature-Aware-Binning-for-Individual-Uncertainty-Calibration
☆13Updated 2 years ago
Alternatives and similar repositories for Tree-Based-Feature-Aware-Binning-for-Individual-Uncertainty-Calibration:
Users that are interested in Tree-Based-Feature-Aware-Binning-for-Individual-Uncertainty-Calibration are comparing it to the libraries listed below
- PyTorch implementation of delayed-feedback-model (DFM)☆14Updated 2 years ago
- ☆11Updated 3 years ago
- code of Generalized Delayed Feedback Model with Post-Click Information in Recommender Systems, NeurIPS 2022☆10Updated 2 years ago
- ☆18Updated 6 years ago
- ☆15Updated 3 years ago
- ☆70Updated 4 years ago
- code of our WWW 2022 paper Asymptotically Unbiased Estimation for Delayed Feedback Modeling via Label Correction☆28Updated 2 years ago
- code for ResSys'18 paper: "Exploring Recommendations Under User-Controlled Data Filtering"☆23Updated 6 years ago
- Content-aware Neural Hashing for Cold-start Recommendation. SIGIR 2020☆19Updated 4 years ago
- ☆24Updated 3 years ago
- ☆10Updated 4 years ago
- ☆39Updated last month
- Uncovering User Interest from Biased and Noised Watch Time in Video Recommendation. In Recsys23.☆10Updated last year
- ☆11Updated 5 years ago
- Bayesian Personalized Ranking Model with Attribute-to-Feature Mappings for Cold-Start Recommendation☆16Updated 9 years ago
- Implementation of SetRank in SIGIR 2020☆51Updated 4 years ago
- ☆15Updated 5 months ago
- This is an official implementation for "Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertisin…☆55Updated 2 years ago
- Multi-order Attentive Ranking Model for Sequential Recommendation☆26Updated 5 years ago
- This is the implementation of `Towards Understanding the Overfitting Phenomenon of Deep Click-Through Rate Models`, which is accepted by …☆25Updated 2 years ago
- ☆24Updated 8 years ago
- This is the implementation code for the WWW2021 paper "Variation Control and Evaluation for Generative Slate Recommendation"☆13Updated 3 years ago
- A novel dynamic recommendation model that focuses on users who have interactions in the past but turn relatively inactive recently☆14Updated 2 years ago
- ☆31Updated last year
- ☆61Updated 3 years ago
- ☆9Updated last year
- An implementation of RaFM. Xiaoshuang Chen, Yin Zheng, Jiaxiang Wang, et al. "RaFM: Rank-Aware Factorization Machines"☆12Updated 5 years ago
- [WWW'22] Deep Interest Highlight Network for Click-Through Rate Prediction in Trigger-Induced Recommendation☆22Updated 2 years ago
- ☆13Updated 3 years ago
- ☆18Updated 3 years ago