Cover Image

A PID-Controlled Non-Negative Tensor Factorization Model for Analyzing Missing Data in NILM

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Shi, DengYu
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Latent Tensor Factorization with Nonlinear PID Control for Missing Data Recovery in Non-Intrusive Load Monitoring
by: Wang, Yiran, et al.
Published: (2025)

A PID-Controlled Tensor Wheel Decomposition Model for Dynamic Link Prediction
by: Wang, Qu, et al.
Published: (2025)

Benchmarking Active Learning for NILM
by: Patel, Dhruv, et al.
Published: (2024)

Water Quality Data Imputation via A Fast Latent Factorization of Tensors with PID-based Optimizer
by: Liu, Qian, et al.
Published: (2025)

Stratified Non-Negative Tensor Factorization
by: Sietsema, Alexander, et al.
Published: (2024)

DP$^2$-NILM: A Distributed and Privacy-preserving Framework for Non-intrusive Load Monitoring
by: Dai, Shuang, et al.
Published: (2022)

Dynamic QoS Prediction via a Non-Negative Tensor Snowflake Factorization
by: Xia, YongHui, et al.
Published: (2025)

Fusion-ResNet: A Lightweight multi-label NILM Model Using PCA-ICA Feature Fusion
by: Hoosh, Sahar Moghimian, et al.
Published: (2025)

Missing Data Imputation Based on Dynamically Adaptable Structural Equation Modeling with Self-Attention
by: Deng, Ou, et al.
Published: (2023)

Algorithms for Non-Negative Matrix Factorization on Noisy Data With Negative Values
by: Green, Dylan, et al.
Published: (2023)

Uncovering Model Processing Strategies with Non-Negative Per-Example Fisher Factorization
by: Matena, Michael, et al.
Published: (2023)

Factor Augmented Tensor-on-Tensor Neural Networks
by: Zhou, Guanhao, et al.
Published: (2024)

PSLF: A PID Controller-incorporated Second-order Latent Factor Analysis Model for Recommender System
by: Wang, Jialiang, et al.
Published: (2024)

Noisy Nonnegative Tucker Decomposition with Sparse Factors and Missing Data
by: Zhang, Xiongjun, et al.
Published: (2022)

Data-Driven Adaptive PID Control Based on Physics-Informed Neural Networks
by: Ito, Junsei, et al.
Published: (2025)

DiffPuter: Empowering Diffusion Models for Missing Data Imputation
by: Zhang, Hengrui, et al.
Published: (2024)

Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e
by: Xu, Chenwei, et al.
Published: (2023)

Finding Rule-Interpretable Non-Negative Data Representation
by: Mihelčić, Matej, et al.
Published: (2022)

Learnable Similarity and Dissimilarity Guided Symmetric Non-Negative Matrix Factorization
by: Lyu, Wenlong, et al.
Published: (2024)

Interpretable Multi-View Clustering Based on Anchor Graph Tensor Factorization
by: Wang, Rui, et al.
Published: (2024)

GSVD-NMF: Recovering Missing Features in Non-negative Matrix Factorization
by: Guo, Youdong, et al.
Published: (2024)

Extending Model-x Framework to Missing Data
by: Koyuncu, Deniz, et al.
Published: (2022)

Order-Agnostic Autoregressive Modelling with Missing Data
by: Peis, Ignacio, et al.
Published: (2026)

The Target Polish: A New Approach to Outlier-Resistant Non-Negative Matrix Factorization
by: Fogel, Paul, et al.
Published: (2025)

Scalable Bayesian Tensor Ring Factorization for Multiway Data Analysis
by: Tao, Zerui, et al.
Published: (2024)

Panda: Test-Time Adaptation with Negative Data Augmentation
by: Deng, Ruxi, et al.
Published: (2025)

Personalized Tucker Decomposition: Modeling Commonality and Peculiarity on Tensor Data
by: Hu, Jiuyun, et al.
Published: (2023)

PID-Guided Partial Alignment for Multimodal Decentralized Federated Learning
by: Shi, Yanhang, et al.
Published: (2026)

Real-Time Network Traffic Forecasting with Missing Data: A Generative Model Approach
by: Deng, Lei, et al.
Published: (2025)

Wild Bootstrap Inference for Non-Negative Matrix Factorization with Random Effects
by: Satoh, Kenichi
Published: (2026)

Deep Generative Imputation Model for Missing Not At Random Data
by: Chen, Jialei, et al.
Published: (2023)

Causal and Counterfactual Views of Missing Data Models
by: Nabi, Razieh, et al.
Published: (2022)

Semi-supervised Symmetric Non-negative Matrix Factorization with Low-Rank Tensor Representation
by: Jia, Yuheng, et al.
Published: (2024)

Non-Negative Matrix Factorization Using Non-Von Neumann Computers
by: Borle, Ajinkya, et al.
Published: (2025)

Latent Diffusion for Missing Data
by: Estad, Alberte Heering, et al.
Published: (2026)

Privacy Amplification by Missing Data
by: Roburin, Simon, et al.
Published: (2026)

Missing Data Imputation by Reducing Mutual Information with Rectified Flows
by: Yu, Jiahao, et al.
Published: (2025)

Analyzing Political Text at Scale with Online Tensor LDA
by: Kangaslahti, Sara, et al.
Published: (2025)

Doubly Calibrated Estimator for Recommendation on Data Missing Not At Random
by: Kweon, Wonbin, et al.
Published: (2024)

Large Language Models for Missing Data Imputation: Understanding Behavior, Hallucination Effects, and Control Mechanisms
by: Mangussi, Arthur Dantas, et al.
Published: (2026)