Imagen de Portada

EMERS: Energy Meter for Recommender Systems

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Wegmeth, Lukas, Vente, Tobias, Said, Alan, Beel, Joeran
Formato:	Preprint
Publicado:	2024
Materias:	Information Retrieval
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

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

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

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

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

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

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

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

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

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

Algorithm Selection for Recommender Systems via Meta-Learning on Algorithm Characteristics
por: Decker, Jarne Mathi, et al.
Publicado: (2025)

Ensemble Boost: Greedy Selection for Superior Recommender Systems
por: Mehta, Zainil, et al.
Publicado: (2024)

Evaluating Sakana's AI Scientist: Bold Claims, Mixed Results, and a Promising Future?
por: Beel, Joeran, et al.
Publicado: (2025)

Recommender Systems for Social Good: The Role of Accountability and Sustainability
por: Said, Alan
Publicado: (2025)

The Hidden Cost of Defaults in Recommender System Evaluation
por: Berling, Hannah, et al.
Publicado: (2025)

Early Explorations of Recommender Systems for Physical Activity and Well-being
por: Said, Alan
Publicado: (2025)

Understanding Fairness in Recommender Systems: A Healthcare Perspective
por: Kecki, Veronica, et al.
Publicado: (2024)

From Theory to Practice: Implementing and Evaluating e-Fold Cross-Validation
por: Mahlich, Christopher, et al.
Publicado: (2024)

On Explaining Recommendations with Large Language Models: A Review
por: Said, Alan
Publicado: (2024)

We're Still Doing It (All) Wrong: Recommender Systems, Fifteen Years Later
por: Said, Alan, et al.
Publicado: (2025)

On the Reliability of Sampling Strategies in Offline Recommender Evaluation
por: Pereira, Bruno L., et al.
Publicado: (2025)

Pairwise Ranking Loss for Multi-Task Learning in Recommender Systems
por: Durmus, Furkan, et al.
Publicado: (2024)

Towards Carbon Footprint-Aware Recommender Systems for Greener Item Recommendation
por: Kalisvaart, Raoul, et al.
Publicado: (2025)

Tell Me the Good Stuff: User Preferences in Movie Recommendation Explanations
por: Ahmad, Juan, et al.
Publicado: (2025)

A Survey of Latent Factor Models in Recommender Systems
por: Alshbanat, Hind I., et al.
Publicado: (2024)

Recommender Systems for Good (RS4Good): Survey of Use Cases and a Call to Action for Research that Matters
por: Jannach, Dietmar, et al.
Publicado: (2024)

Effects of Using Synthetic Data on Deep Recommender Models' Performance
por: Taskin, Fatih Cihan, et al.
Publicado: (2024)

Soundtracks of Our Lives: How Age Influences Musical Preferences
por: Golubovikj, Arsen Matej, et al.
Publicado: (2025)

Socially-Aware Recommender Systems Mitigate Opinion Clusterization
por: Schüepp, Lukas, et al.
Publicado: (2026)

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

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

Federated Conversational Recommender System
por: Lin, Allen, et al.
Publicado: (2025)

Deep Research for Recommender Systems
por: Ou, Kesha, et al.
Publicado: (2026)

Emotion-based Recommender System
por: Wang, Hao
Publicado: (2025)

Generative Conversational Recommender System
por: Zhang, Sixiao, et al.
Publicado: (2026)

Implementation of Recommendation Algorithm based on Recommendation Sessions in E-commerce IT System
por: Malinowski, Michał
Publicado: (2024)

Continual Collaborative Distillation for Recommender System
por: Lee, Gyuseok, et al.
Publicado: (2024)

Transparency, Privacy, and Fairness in Recommender Systems
por: Kowald, Dominik
Publicado: (2024)

Snippet-based Conversational Recommender System
por: Sun, Haibo, et al.
Publicado: (2024)

Data Watermarking for Sequential Recommender Systems
por: Zhang, Sixiao, et al.
Publicado: (2024)