Cover Image

A Survey on Deep Neural Networks in Collaborative Filtering Recommendation Systems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Pang, Noah, Shahrul Azman Mohd, Sarim, Hafiz Mohd
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Convolutional Transformer Neural Collaborative Filtering
by: Li, Pang, et al.
Published: (2024)

Non-Interfering Weight Fields: Treating Model Parameters as a Continuously Extensible Function
by: Chaudhry, Sarim
Published: (2026)

Recursive Concept Evolution for Compositional Reasoning in Large Language Models
by: Chaudhry, Sarim
Published: (2026)

Learning to Fast Unrank in Collaborative Filtering Recommendation
by: Zhao, Junpeng, et al.
Published: (2025)

Low-bit Model Quantization for Deep Neural Networks: A Survey
by: Liu, Kai, et al.
Published: (2025)

Proximity-Informed Calibration for Deep Neural Networks
by: Xiong, Miao, et al.
Published: (2023)

Deep Model Merging: The Sister of Neural Network Interpretability -- A Survey
by: Khan, Arham, et al.
Published: (2024)

Online and Offline Evaluations of Collaborative Filtering and Content Based Recommender Systems
by: Elahi, Ali, et al.
Published: (2024)

SF-GNN: Self Filter for Message Lossless Propagation in Deep Graph Neural Network
by: Zhu, Yushan, et al.
Published: (2024)

From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks
by: Geng, Xue, et al.
Published: (2024)

Parameter-Efficient Fine-Tuning for Low-Resource Languages: A Comparative Study of LLMs for Bengali Hate Speech Detection
by: Islam, Akif, et al.
Published: (2025)

Deep Graph Anomaly Detection: A Survey and New Perspectives
by: Qiao, Hezhe, et al.
Published: (2024)

A Survey of Route Recommendations: Methods, Applications, and Opportunities
by: Zhang, Shiming, et al.
Published: (2024)

Generalization in Neural Networks: A Broad Survey
by: Rohlfs, Chris
Published: (2022)

A Survey on Knowledge Editing of Neural Networks
by: Mazzia, Vittorio, et al.
Published: (2023)

Neural Combinatorial Clustered Bandits for Recommendation Systems
by: Atalar, Baran, et al.
Published: (2024)

Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective
by: Dong, Yushun, et al.
Published: (2024)

Rethinking Spectral Graph Neural Networks with Spatially Adaptive Filtering
by: Guo, Jingwei, et al.
Published: (2024)

A Survey on Popularity Bias in Recommender Systems
by: Klimashevskaia, Anastasiia, et al.
Published: (2023)

Weightless Neural Networks for Continuously Trainable Personalized Recommendation Systems
by: Latif, Rafayel, et al.
Published: (2025)

Compositional Function Networks: A High-Performance Alternative to Deep Neural Networks with Built-in Interpretability
by: Li, Fang
Published: (2025)

A Comprehensive Survey on Self-Interpretable Neural Networks
by: Ji, Yang, et al.
Published: (2025)

Adaptive Physics-informed Neural Networks: A Survey
by: Torres, Edgar, et al.
Published: (2025)

Certifying Global Robustness for Deep Neural Networks
by: Li, You, et al.
Published: (2024)

Neural Bayesian Filtering
by: Solinas, Christopher, et al.
Published: (2025)

Mobile Network Configuration Recommendation using Deep Generative Graph Neural Network
by: Piroti, Shirwan, et al.
Published: (2024)

On the Mechanisms of Collaborative Learning in VAE Recommenders
by: Vuong, Tung-Long, et al.
Published: (2025)

Emergent Symbol-like Number Variables in Artificial Neural Networks
by: Grant, Satchel, et al.
Published: (2025)

Exploring and Exploiting the Asymmetric Valley of Deep Neural Networks
by: Li, Xin-Chun, et al.
Published: (2024)

A Survey on Multi-Resident Activity Recognition in Smart Environments
by: Shiri, Farhad MortezaPour, et al.
Published: (2023)

Deep Neural Networks as Discrete Dynamical Systems: Implications for Physics-Informed Learning
by: Ganguly, Abhisek, et al.
Published: (2026)

Survey on Generalization Theory for Graph Neural Networks
by: Vasileiou, Antonis, et al.
Published: (2025)

A Survey on State-of-the-art Deep Learning Applications and Challenges
by: Noor, Mohd Halim Mohd, et al.
Published: (2024)

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

A Comprehensive Survey of Evaluation Techniques for Recommendation Systems
by: Jadon, Aryan, et al.
Published: (2023)

Relational Composition in Neural Networks: A Survey and Call to Action
by: Wattenberg, Martin, et al.
Published: (2024)

iPINNER: An Iterative Physics-Informed Neural Network with Ensemble Kalman Filter
by: Lu, Binghang, et al.
Published: (2025)

Wormhole Dynamics in Deep Neural Networks
by: Lai, Yen-Lung, et al.
Published: (2025)

Deep Reinforcement Learning for Demand Driven Services in Logistics and Transportation Systems: A Survey
by: Zong, Zefang, et al.
Published: (2021)

A Survey of Personalized Federated Foundation Models for Privacy-Preserving Recommendation
by: Li, Zhiwei, et al.
Published: (2025)