Learning Cascade Ranking as One Network
Fuente:
arXiv
Guardado en:
| Autores principales: | Wang, Yunli, Zhang, Zhen, Wang, Zhiqiang, Yang, Zixuan, Li, Yu, Yang, Jian, Wen, Shiyang, Jiang, Peng, Gai, Kun |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Scaling Laws for Online Advertisement Retrieval
por: Wang, Yunli, et al.
Publicado: (2024)
por: Wang, Yunli, et al.
Publicado: (2024)
Adaptive Neural Ranking Framework: Toward Maximized Business Goal for Cascade Ranking Systems
por: Wang, Yunli, et al.
Publicado: (2023)
por: Wang, Yunli, et al.
Publicado: (2023)
AURO: Reinforcement Learning for Adaptive User Retention Optimization in Recommender Systems
por: Xue, Zhenghai, et al.
Publicado: (2023)
por: Xue, Zhenghai, et al.
Publicado: (2023)
Enhancing Interpretability and Effectiveness in Recommendation with Numerical Features via Learning to Contrast the Counterfactual samples
por: Xu, Xiaoxiao, et al.
Publicado: (2025)
por: Xu, Xiaoxiao, et al.
Publicado: (2025)
Multi-Epoch learning with Data Augmentation for Deep Click-Through Rate Prediction
por: Fan, Zhongxiang, et al.
Publicado: (2024)
por: Fan, Zhongxiang, et al.
Publicado: (2024)
HoME: Hierarchy of Multi-Gate Experts for Multi-Task Learning at Kuaishou
por: Wang, Xu, et al.
Publicado: (2024)
por: Wang, Xu, et al.
Publicado: (2024)
CaliCausalRank: Calibrated Multi-Objective Ad Ranking with Robust Counterfactual Utility Optimization
por: Yang, Xikai, et al.
Publicado: (2026)
por: Yang, Xikai, et al.
Publicado: (2026)
Generative Recommendation for Large-Scale Advertising
por: Xue, Ben, et al.
Publicado: (2026)
por: Xue, Ben, et al.
Publicado: (2026)
Generative Auto-Bidding with Value-Guided Explorations
por: Gao, Jingtong, et al.
Publicado: (2025)
por: Gao, Jingtong, et al.
Publicado: (2025)
RankGraph: Unified Heterogeneous Graph Learning for Cross-Domain Recommendation
por: Wu, Renzhi, et al.
Publicado: (2025)
por: Wu, Renzhi, et al.
Publicado: (2025)
Unlearning for Federated Online Learning to Rank: A Reproducibility Study
por: Tao, Yiling, et al.
Publicado: (2025)
por: Tao, Yiling, et al.
Publicado: (2025)
Blending Learning to Rank and Dense Representations for Efficient and Effective Cascades
por: Nardini, Franco Maria, et al.
Publicado: (2025)
por: Nardini, Franco Maria, et al.
Publicado: (2025)
Adaptive Convolutional Forecasting Network Based on Time Series Feature-Driven
por: Zhang, Dandan, et al.
Publicado: (2024)
por: Zhang, Dandan, et al.
Publicado: (2024)
Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation
por: Gomez, Camilo, et al.
Publicado: (2026)
por: Gomez, Camilo, et al.
Publicado: (2026)
Creator-Side Recommender System: Challenges, Designs, and Applications
por: Chen, Xiaoshuang, et al.
Publicado: (2025)
por: Chen, Xiaoshuang, et al.
Publicado: (2025)
Deep Evolutional Instant Interest Network for CTR Prediction in Trigger-Induced Recommendation
por: Xiao, Zhibo, et al.
Publicado: (2024)
por: Xiao, Zhibo, et al.
Publicado: (2024)
A Self-boosted Framework for Calibrated Ranking
por: Zhang, Shunyu, et al.
Publicado: (2024)
por: Zhang, Shunyu, et al.
Publicado: (2024)
RPAF: A Reinforcement Prediction-Allocation Framework for Cache Allocation in Large-Scale Recommender Systems
por: Su, Shuo, et al.
Publicado: (2024)
por: Su, Shuo, et al.
Publicado: (2024)
Two-Stage Constrained Actor-Critic for Short Video Recommendation
por: Cai, Qingpeng, et al.
Publicado: (2023)
por: Cai, Qingpeng, et al.
Publicado: (2023)
Residual Multi-Task Learner for Applied Ranking
por: Fu, Cong, et al.
Publicado: (2024)
por: Fu, Cong, et al.
Publicado: (2024)
Do Not Wait: Learning Re-Ranking Model Without User Feedback At Serving Time in E-Commerce
por: Wang, Yuan, et al.
Publicado: (2024)
por: Wang, Yuan, et al.
Publicado: (2024)
Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential Recommendation
por: Wei, Shaowei, et al.
Publicado: (2024)
por: Wei, Shaowei, et al.
Publicado: (2024)
RewardRank: Optimizing True Learning-to-Rank Utility
por: Bhatt, Gaurav, et al.
Publicado: (2025)
por: Bhatt, Gaurav, et al.
Publicado: (2025)
RRCM: Ranking-Driven Retrieval over Collaborative and Meta Memories for LLM Recommendation
por: Li, Shijun, et al.
Publicado: (2026)
por: Li, Shijun, et al.
Publicado: (2026)
Adaptive$^2$: Adaptive Domain Mining for Fine-grained Domain Adaptation Modeling
por: Sun, Wenxuan, et al.
Publicado: (2024)
por: Sun, Wenxuan, et al.
Publicado: (2024)
Generative Pre-trained Ranking Model with Over-parameterization at Web-Scale (Extended Abstract)
por: Li, Yuchen, et al.
Publicado: (2024)
por: Li, Yuchen, et al.
Publicado: (2024)
Taming Recommendation Bias with Causal Intervention on Evolving Personal Popularity
por: Tan, Shiyin, et al.
Publicado: (2025)
por: Tan, Shiyin, et al.
Publicado: (2025)
Hierarchical Multi-Interest Co-Network For Coarse-Grained Ranking
por: Yuan, Xu, et al.
Publicado: (2022)
por: Yuan, Xu, et al.
Publicado: (2022)
UniPinRec: Unifying Generative Retrieval and Ranking at Pinterest Scale
por: Li, Hanyu, et al.
Publicado: (2026)
por: Li, Hanyu, et al.
Publicado: (2026)
An Efficient Continuous Control Perspective for Reinforcement-Learning-based Sequential Recommendation
por: Wang, Jun, et al.
Publicado: (2024)
por: Wang, Jun, et al.
Publicado: (2024)
Proximal Ranking Policy Optimization for Practical Safety in Counterfactual Learning to Rank
por: Gupta, Shashank, et al.
Publicado: (2024)
por: Gupta, Shashank, et al.
Publicado: (2024)
RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank
por: Chowdhury, Tanya, et al.
Publicado: (2024)
por: Chowdhury, Tanya, et al.
Publicado: (2024)
Towards More Robust and Accurate Sequential Recommendation with Cascade-guided Adversarial Training
por: Tan, Juntao, et al.
Publicado: (2023)
por: Tan, Juntao, et al.
Publicado: (2023)
DeepMTL2R: A Library for Deep Multi-task Learning to Rank
por: Dong, Chaosheng, et al.
Publicado: (2026)
por: Dong, Chaosheng, et al.
Publicado: (2026)
DTN: Deep Multiple Task-specific Feature Interactions Network for Multi-Task Recommendation
por: Bi, Yaowen, et al.
Publicado: (2024)
por: Bi, Yaowen, et al.
Publicado: (2024)
AdaS&S: a One-Shot Supernet Approach for Automatic Embedding Size Search in Deep Recommender System
por: Wei, He, et al.
Publicado: (2024)
por: Wei, He, et al.
Publicado: (2024)
Estimating the Hessian Matrix of Ranking Objectives for Stochastic Learning to Rank with Gradient Boosted Trees
por: Kang, Jingwei, et al.
Publicado: (2024)
por: Kang, Jingwei, et al.
Publicado: (2024)
Enhancing Travel Decision-Making: A Contrastive Learning Approach for Personalized Review Rankings in Accommodations
por: Igebaria, Reda, et al.
Publicado: (2024)
por: Igebaria, Reda, et al.
Publicado: (2024)
Knowledge Graph Context-Enhanced Diversified Recommendation
por: Liu, Xiaolong, et al.
Publicado: (2023)
por: Liu, Xiaolong, et al.
Publicado: (2023)
Mixed Supervised Graph Contrastive Learning for Recommendation
por: Zhang, Weizhi, et al.
Publicado: (2024)
por: Zhang, Weizhi, et al.
Publicado: (2024)
Ejemplares similares
-
Scaling Laws for Online Advertisement Retrieval
por: Wang, Yunli, et al.
Publicado: (2024) -
Adaptive Neural Ranking Framework: Toward Maximized Business Goal for Cascade Ranking Systems
por: Wang, Yunli, et al.
Publicado: (2023) -
AURO: Reinforcement Learning for Adaptive User Retention Optimization in Recommender Systems
por: Xue, Zhenghai, et al.
Publicado: (2023) -
Enhancing Interpretability and Effectiveness in Recommendation with Numerical Features via Learning to Contrast the Counterfactual samples
por: Xu, Xiaoxiao, et al.
Publicado: (2025) -
Multi-Epoch learning with Data Augmentation for Deep Click-Through Rate Prediction
por: Fan, Zhongxiang, et al.
Publicado: (2024)