Cover Image

Maximum Impact with Fewer Features: Efficient Feature Selection for Cold-Start Recommenders through Collaborative Importance Weighting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sukhorukov, Nikita, Gusak, Danil, Frolov, Evgeny
Format:	Preprint
Published:	2025
Subjects:	Information Retrieval Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Recommendation Is a Dish Better Served Warm
by: Gusak, Danil, et al.
Published: (2025)

Scalable Cross-Entropy Loss for Sequential Recommendations with Large Item Catalogs
by: Mezentsev, Gleb, et al.
Published: (2024)

RECE: Reduced Cross-Entropy Loss for Large-Catalogue Sequential Recommenders
by: Gusak, Danil, et al.
Published: (2024)

Time to Split: Exploring Data Splitting Strategies for Offline Evaluation of Sequential Recommenders
by: Gusak, Danil, et al.
Published: (2025)

SplitLight: An Exploratory Toolkit for Recommender Systems Datasets and Splits
by: Volodkevich, Anna, et al.
Published: (2026)

Ultra Fast Warm Start Solution for Graph Recommendations
by: Yusupov, Viacheslav, et al.
Published: (2025)

Autoregressive Generation Strategies for Top-K Sequential Recommendations
by: Volodkevich, Anna, et al.
Published: (2024)

Contrastive Learning for Cold Start Recommendation with Adaptive Feature Fusion
by: Hu, Jiacheng, et al.
Published: (2025)

Shallow AutoEncoding Recommender with Cold Start Handling via Side Features
by: Cui, Edward DongBo, et al.
Published: (2025)

Addressing Cold Start For next-article Recommendation
by: Elgohary, Omar, et al.
Published: (2025)

Warmer for Less: A Cost-Efficient Strategy for Cold-Start Recommendations at Pinterest
by: Ebrahimi, Saeed, et al.
Published: (2025)

Leveraging Geometric Insights in Hyperbolic Triplet Loss for Improved Recommendations
by: Yusupov, Viacheslav, et al.
Published: (2025)

Efficient Cold-Start Recommendation via BPE Token-Level Embedding Initialization with LLM
by: Zhao, Yushang, et al.
Published: (2025)

FELRec: Efficient Handling of Item Cold-Start With Dynamic Representation Learning in Recommender Systems
by: Weimann, Kuba, et al.
Published: (2022)

End-to-End Graph-Sequential Representation Learning for Accurate Recommendations
by: Baikalov, Vladimir, et al.
Published: (2024)

Position-Aware Sequential Attention for Accurate Next Item Recommendations
by: Nabiev, Timur, et al.
Published: (2026)

MoToRec: Sparse-Regularized Multimodal Tokenization for Cold-Start Recommendation
by: Liu, Jialin, et al.
Published: (2026)

Revealing Potential Biases in LLM-Based Recommender Systems in the Cold Start Setting
by: Andre, Alexandre, et al.
Published: (2025)

Metric Learning for Tag Recommendation: Tackling Data Sparsity and Cold Start Issues
by: Luo, Yuanshuai, et al.
Published: (2024)

IDProxy: Cold-Start CTR Prediction for Ads and Recommendation at Xiaohongshu with Multimodal LLMs
by: Zhang, Yubin, et al.
Published: (2026)

RAGSys: Item-Cold-Start Recommender as RAG System
by: Contal, Emile, et al.
Published: (2024)

Pairwise and Attribute-Aware Decision Tree-Based Preference Elicitation for Cold-Start Recommendation
by: Gharahighehi, Alireza, et al.
Published: (2025)

Context Features Are Cheap: Rank-Aware Decomposition for Efficient Feature Interaction in Recommender Systems
by: Tkach, Yevgeny
Published: (2026)

DisCo: Graph-Based Disentangled Contrastive Learning for Cold-Start Cross-Domain Recommendation
by: Li, Hourun, et al.
Published: (2024)

FairFS: Addressing Deep Feature Selection Biases for Recommender System
by: Wang, Xianquan, et al.
Published: (2026)

Causal Feature Selection Method for Contextual Multi-Armed Bandits in Recommender System
by: Zhao, Zhenyu, et al.
Published: (2024)

Cross-Representation Knowledge Transfer for Improved Sequential Recommendations
by: Gimranov, Artur, et al.
Published: (2026)

Let It Go? Not Quite: Addressing Item Cold Start in Sequential Recommendations with Content-Based Initialization
by: Pembek, Anton, et al.
Published: (2025)

Parameter-Efficient Single Collaborative Branch for Recommendation
by: Moscati, Marta, et al.
Published: (2025)

CoRA: Collaborative Information Perception by Large Language Model's Weights for Recommendation
by: Liu, Yuting, et al.
Published: (2024)

ID Embedding as Subtle Features of Content and Structure for Multimodal Recommendation
by: Liu, Yuting, et al.
Published: (2023)

Retrievable Domain-Sensitive Feature Memory for Multi-Domain Recommendation
by: Zhao, Yuang, et al.
Published: (2024)

Broad Recommender System: An Efficient Nonlinear Collaborative Filtering Approach
by: Huang, Ling, et al.
Published: (2022)

A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios
by: Ganhör, Christian, et al.
Published: (2024)

Diagnosing LLM-based Rerankers in Cold-Start Recommender Systems: Coverage, Exposure and Practical Mitigations
by: Lemdiasova, Ekaterina, et al.
Published: (2026)

Knowledge Graph Completion with Mixed Geometry Tensor Factorization
by: Yusupov, Viacheslav, et al.
Published: (2025)

Language-Model Prior Overcomes Cold-Start Items
by: Wang, Shiyu, et al.
Published: (2024)

Cold-start Recommendation by Personalized Embedding Region Elicitation
by: Nguyen, Hieu Trung, et al.
Published: (2024)

Efficient Dataset Selection for Continual Adaptation of Generative Recommenders
by: Jiao, Cathy, et al.
Published: (2026)

A Counterfactual Approach for Addressing Individual User Unfairness in Collaborative Recommender System
by: Baidya, Nikita, et al.
Published: (2026)