:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Mehta, Zainil, Vente, Tobias
Format:	Preprint
Published:	2024
Subjects:	Information Retrieval
Online Access:	https://arxiv.org/abs/2407.05221
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Recommender Systems Algorithm Selection for Ranking Prediction on Implicit Feedback Datasets
by: Wegmeth, Lukas, et al.
Published: (2024)

The Potential of AutoML for Recommender Systems
by: Vente, Tobias, et al.
Published: (2024)

Revealing the Hidden Impact of Top-N Metrics on Optimization in Recommender Systems
by: Wegmeth, Lukas, et al.
Published: (2024)

EMERS: Energy Meter for Recommender Systems
by: Wegmeth, Lukas, et al.
Published: (2024)

From Clicks to Carbon: The Environmental Toll of Recommender Systems
by: Vente, Tobias, et al.
Published: (2024)

Green Recommender Systems: Optimizing Dataset Size for Energy-Efficient Algorithm Performance
by: Arabzadeh, Ardalan, et al.
Published: (2024)

Green Recommender Systems: Understanding and Minimizing the Carbon Footprint of AI-Powered Personalization
by: Wegmeth, Lukas, et al.
Published: (2025)

e-Fold Cross-Validation for Recommender-System Evaluation
by: Baumgart, Moritz, et al.
Published: (2024)

APS Explorer: Navigating Algorithm Performance Spaces for Informed Dataset Selection
by: Vente, Tobias, et al.
Published: (2025)

From AutoRecSys to AutoRecLab: A Call to Build, Evaluate, and Govern Autonomous Recommender-Systems Research Labs
by: Beel, Joeran, et al.
Published: (2025)

HELM: A Human-Centered Evaluation Framework for LLM-Powered Recommender Systems
by: Mehta, Sushant
Published: (2026)

UMRE: A Unified Monotonic Transformation for Ranking Ensemble in Recommender Systems
by: Xu, Zhengrui, et al.
Published: (2025)

Evaluating Ensemble Methods for News Recommender Systems
by: Gray, Alexander, et al.
Published: (2024)

The Environmental Impact of Ensemble Techniques in Recommender Systems
by: Nitschke, Jannik
Published: (2025)

Understand your Users, An Ensemble Learning Framework for Natural Noise Filtering in Recommender Systems
by: Hawat, Clarita, et al.
Published: (2025)

MATRAG: Multi-Agent Transparent Retrieval-Augmented Generation for Explainable Recommendations
by: Mehta, Sushant
Published: (2026)

Rethinking Recommender Systems: Cluster-based Algorithm Selection
by: Lizenberger, Andreas, et al.
Published: (2024)

Rethinking Multi-objective Ranking Ensemble in Recommender System: From Score Fusion to Rank Consistency
by: Xia, Boyang, et al.
Published: (2026)

AEFS: Adaptive Early Feature Selection for Deep Recommender Systems
by: Hu, Fan, et al.
Published: (2025)

Ensembles at Any Cost? Accuracy-Energy Trade-offs in Recommender Systems
by: Nitschke, Jannik, et al.
Published: (2026)

Toward Holistic Evaluation of Recommender Systems Powered by Generative Models
by: Deldjoo, Yashar, et al.
Published: (2025)

An End-to-End Multi-objective Ensemble Ranking Framework for Video Recommendation
by: He, Tiantian, et al.
Published: (2025)

Corpus Poisoning via Approximate Greedy Gradient Descent
by: Su, Jinyan, et al.
Published: (2024)

FLAME: Condensing Ensemble Diversity into a Single Network for Efficient Sequential Recommendation
by: Kim, WooJoo, et al.
Published: (2026)

Boosting Parameter Efficiency in LLM-Based Recommendation through Sophisticated Pruning
by: Zheng, Shanle, et al.
Published: (2025)

SELF: Surrogate-light Feature Selection with Large Language Models in Deep Recommender Systems
by: Jia, Pengyue, et al.
Published: (2024)

Hybrid Cold-Start Recommender System for Closure Model Selection in Multiphase Flow Simulations
by: Hänsch, S., et al.
Published: (2026)

CRUISE on Quantum Computing for Feature Selection in Recommender Systems
by: Niu, Jiayang, et al.
Published: (2024)

Aligning Large Language Models with Recommendation Knowledge
by: Cao, Yuwei, et al.
Published: (2024)

GORACS: Group-level Optimal Transport-guided Coreset Selection for LLM-based Recommender Systems
by: Mei, Tiehua, et al.
Published: (2025)

ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems
by: Jia, Pengyue, et al.
Published: (2024)

Active Learning via Classifier Impact and Greedy Selection for Interactive Image Retrieval
by: Bar, Leah, et al.
Published: (2024)

Rethinking Recommendation Paradigms: From Pipelines to Agentic Recommender Systems
by: Hu, Jinxin, et al.
Published: (2026)

Epistemic Uncertainty-aware Recommendation Systems via Bayesian Deep Ensemble Learning
by: Cheraghi, Radin, et al.
Published: (2025)

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

Hesitation and Tolerance in Recommender Systems
by: Zou, Kuan, et al.
Published: (2024)

Federated Conversational Recommender System
by: Lin, Allen, et al.
Published: (2025)

Deep Research for Recommender Systems
by: Ou, Kesha, et al.
Published: (2026)

Emotion-based Recommender System
by: Wang, Hao
Published: (2025)

Generative Conversational Recommender System
by: Zhang, Sixiao, et al.
Published: (2026)