Saved in:
| Main Authors: | Saha, Aadirupa, Gaillard, Pierre |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.18917 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Low-Rank Online Dynamic Assortment with Dual Contextual Information
by: Lee, Seong Jin, et al.
Published: (2024)
by: Lee, Seong Jin, et al.
Published: (2024)
Towards Efficient Pareto-optimal Utility-Fairness between Groups in Repeated Rankings
by: Mai, Phuong Dinh, et al.
Published: (2024)
by: Mai, Phuong Dinh, et al.
Published: (2024)
Stop Treating Collisions Equally: Qualification-Aware Semantic ID Learning for Recommendation at Industrial Scale
by: Hu, Zheng, et al.
Published: (2026)
by: Hu, Zheng, et al.
Published: (2026)
Transformers Meet ACT-R: Repeat-Aware and Sequential Listening Session Recommendation
by: Tran, Viet-Anh, et al.
Published: (2024)
by: Tran, Viet-Anh, et al.
Published: (2024)
Proximal Ranking Policy Optimization for Practical Safety in Counterfactual Learning to Rank
by: Gupta, Shashank, et al.
Published: (2024)
by: Gupta, Shashank, et al.
Published: (2024)
Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation
by: Zhang, Weizhi, et al.
Published: (2024)
by: Zhang, Weizhi, et al.
Published: (2024)
Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation
by: Shi, Wentao, et al.
Published: (2024)
by: Shi, Wentao, et al.
Published: (2024)
Social Choice for Heterogeneous Fairness in Recommendation
by: Aird, Amanda, et al.
Published: (2024)
by: Aird, Amanda, et al.
Published: (2024)
Crafting Tomorrow: The Influence of Design Choices on Fresh Content in Social Media Recommendation
by: Saket, Srijan, et al.
Published: (2024)
by: Saket, Srijan, et al.
Published: (2024)
Modeling User Exploration Saturation: When Recommender Systems Should Stop Pushing Novelty
by: Ayiku, Enock O., et al.
Published: (2026)
by: Ayiku, Enock O., et al.
Published: (2026)
Wisdom of the Crowds in Forecasting: Forecast Summarization for Supporting Future Event Prediction
by: Saha, Anisha, et al.
Published: (2025)
by: Saha, Anisha, et al.
Published: (2025)
Optimal Baseline Corrections for Off-Policy Contextual Bandits
by: Gupta, Shashank, et al.
Published: (2024)
by: Gupta, Shashank, et al.
Published: (2024)
Practical and Robust Safety Guarantees for Advanced Counterfactual Learning to Rank
by: Gupta, Shashank, et al.
Published: (2024)
by: Gupta, Shashank, et al.
Published: (2024)
Practical Multi-Task Learning for Rare Conversions in Ad Tech
by: Dishi, Yuval, et al.
Published: (2025)
by: Dishi, Yuval, et al.
Published: (2025)
Do We Trust What They Say or What They Do? A Multimodal User Embedding Provides Personalized Explanations
by: Ren, Zhicheng, et al.
Published: (2024)
by: Ren, Zhicheng, et al.
Published: (2024)
RDSA: A Robust Deep Graph Clustering Framework via Dual Soft Assignment
by: Xiang, Yang, et al.
Published: (2024)
by: Xiang, Yang, et al.
Published: (2024)
Algorithm Adaptation Bias in Recommendation System Online Experiments
by: Zheng, Chen, et al.
Published: (2025)
by: Zheng, Chen, et al.
Published: (2025)
Do Not Wait: Learning Re-Ranking Model Without User Feedback At Serving Time in E-Commerce
by: Wang, Yuan, et al.
Published: (2024)
by: Wang, Yuan, et al.
Published: (2024)
OptDist: Learning Optimal Distribution for Customer Lifetime Value Prediction
by: Weng, Yunpeng, et al.
Published: (2024)
by: Weng, Yunpeng, et al.
Published: (2024)
Towards Lifelong Learning Embeddings: An Algorithmic Approach to Dynamically Extend Embeddings
by: Gomes, Miguel Alves, et al.
Published: (2024)
by: Gomes, Miguel Alves, et al.
Published: (2024)
A Scalable Crawling Algorithm Utilizing Noisy Change-Indicating Signals
by: Busa-Fekete, Róbert, et al.
Published: (2025)
by: Busa-Fekete, Róbert, et al.
Published: (2025)
Advancements in Recommender Systems: A Comprehensive Analysis Based on Data, Algorithms, and Evaluation
by: Ma, Xin, et al.
Published: (2024)
by: Ma, Xin, et al.
Published: (2024)
LLMs as Assessors: Right for the Right Reason?
by: Saha, Sourav, et al.
Published: (2026)
by: Saha, Sourav, et al.
Published: (2026)
Towards Practical Large-scale Dynamical Heterogeneous Graph Embedding: Cold-start Resilient Recommendation
by: Long, Mabiao, et al.
Published: (2025)
by: Long, Mabiao, et al.
Published: (2025)
GEO: Generative Engine Optimization
by: Aggarwal, Pranjal, et al.
Published: (2023)
by: Aggarwal, Pranjal, et al.
Published: (2023)
PSQE: A Theoretical-Practical Approach to Pseudo Seed Quality Enhancement for Unsupervised Multimodal Entity Alignment
by: Hong, Yunpeng, et al.
Published: (2026)
by: Hong, Yunpeng, et al.
Published: (2026)
Drift-Adapter: A Practical Approach to Near Zero-Downtime Embedding Model Upgrades in Vector Databases
by: Vejendla, Harshil
Published: (2025)
by: Vejendla, Harshil
Published: (2025)
EnhancedRL: An Enhanced-State Reinforcement Learning Algorithm for Multi-Task Fusion in Recommender Systems
by: Liu, Peng, et al.
Published: (2024)
by: Liu, Peng, et al.
Published: (2024)
Efficient and Robust Regularized Federated Recommendation
by: Liu, Langming, et al.
Published: (2024)
by: Liu, Langming, et al.
Published: (2024)
ParlayANN: Scalable and Deterministic Parallel Graph-Based Approximate Nearest Neighbor Search Algorithms
by: Manohar, Magdalen Dobson, et al.
Published: (2023)
by: Manohar, Magdalen Dobson, et al.
Published: (2023)
Intelligent Algorithm Selection for Recommender Systems: Meta-Learning via in-depth algorithm feature engineering
by: Decker, Jarne Mathi
Published: (2025)
by: Decker, Jarne Mathi
Published: (2025)
Modeling User Preferences as Distributions for Optimal Transport-Based Cross-Domain Recommendation under Non-Overlapping Settings
by: Xiao, Ziyin, et al.
Published: (2025)
by: Xiao, Ziyin, et al.
Published: (2025)
Parameter-Efficient Single Collaborative Branch for Recommendation
by: Moscati, Marta, et al.
Published: (2025)
by: Moscati, Marta, et al.
Published: (2025)
Efficient Sketching and Nearest Neighbor Search Algorithms for Sparse Vector Sets
by: Bruch, Sebastian, et al.
Published: (2025)
by: Bruch, Sebastian, et al.
Published: (2025)
Position Paper: Why the Shooting in the Dark Method Dominates Recommender Systems Practice; A Call to Abandon Anti-Utopian Thinking
by: Rohde, David
Published: (2024)
by: Rohde, David
Published: (2024)
UnifiedRL: A Reinforcement Learning Algorithm Tailored for Multi-Task Fusion in Large-Scale Recommender Systems
by: Liu, Peng, et al.
Published: (2024)
by: Liu, Peng, et al.
Published: (2024)
Listwise Preference Alignment Optimization for Tail Item Recommendation
by: Li, Zihao, et al.
Published: (2025)
by: Li, Zihao, et al.
Published: (2025)
RewardRank: Optimizing True Learning-to-Rank Utility
by: Bhatt, Gaurav, et al.
Published: (2025)
by: Bhatt, Gaurav, et al.
Published: (2025)
Scalable Bayesian Optimization with Sparse Gaussian Process Models
by: Yang, Ang
Published: (2020)
by: Yang, Ang
Published: (2020)
Optimizing Product Deduplication in E-Commerce with Multimodal Embeddings
by: Kulunk, Aysenur, et al.
Published: (2025)
by: Kulunk, Aysenur, et al.
Published: (2025)
Similar Items
-
Low-Rank Online Dynamic Assortment with Dual Contextual Information
by: Lee, Seong Jin, et al.
Published: (2024) -
Towards Efficient Pareto-optimal Utility-Fairness between Groups in Repeated Rankings
by: Mai, Phuong Dinh, et al.
Published: (2024) -
Stop Treating Collisions Equally: Qualification-Aware Semantic ID Learning for Recommendation at Industrial Scale
by: Hu, Zheng, et al.
Published: (2026) -
Transformers Meet ACT-R: Repeat-Aware and Sequential Listening Session Recommendation
by: Tran, Viet-Anh, et al.
Published: (2024) -
Proximal Ranking Policy Optimization for Practical Safety in Counterfactual Learning to Rank
by: Gupta, Shashank, et al.
Published: (2024)