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Deep Sparse Coding for Non–Intrusive Load Monitoring

https://doi.org/10.1109/tsg.2017.2666220
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
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Nonintrusive load monitoring (NILM) performance evaluation
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A review on buildings energy consumption information
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Nonintrusive disaggregation of residential air-conditioning loads from sub-hourly smart meter data
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A study and a directory of energy consumption data sets of buildings
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HVAC terminal hourly end-use disaggregation in commercial buildings with Fourier series model
inferredcites →https://doi.org/10.1016/s0196-8904(99)00173-9openalex-snapshot
Nonintrusive load disaggregation computer program to estimate the energy consumption of major end uses in residential buildings
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An alternating direction method for total variation denoising
inferredcites →https://doi.org/10.1109/5.192069openalex-snapshot
Nonintrusive appliance load monitoring
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Transient event detection in spectral envelope estimates for nonintrusive load monitoring
inferredcites →https://doi.org/10.1109/61.97667openalex-snapshot
Using appliance signatures for monitoring residential loads at meter panel level
inferredcites →https://doi.org/10.1109/67.795138openalex-snapshot
Nonintrusive monitoring of electric loads
inferredcites →https://doi.org/10.1109/apec.2006.1620777openalex-snapshot
Transient Event Detection for Nonintrusive Load Monitoring and Demand-Side Management Using Voltage Distortion
inferredcites →https://doi.org/10.1109/icassp.2010.5495916openalex-snapshot
Hierarchical dictionary learning for invariant classification
inferredcites →https://doi.org/10.1109/imtc.1994.351862openalex-snapshot
Using neural networks for non-intrusive monitoring of industrial electrical loads
inferredcites →https://doi.org/10.1109/mprv.2010.74openalex-snapshot
Disaggregated End-Use Energy Sensing for the Smart Grid
inferredcites →https://doi.org/10.1109/tii.2014.2361288openalex-snapshot
Nonintrusive Load Monitoring: A Temporal Multilabel Classification Approach
inferredcites →https://doi.org/10.1109/tip.2010.2047910openalex-snapshot
Fast Image Recovery Using Variable Splitting and Constrained Optimization
inferredcites →https://doi.org/10.1109/tip.2016.2624140openalex-snapshot
Weakly Supervised Deep Matrix Factorization for Social Image Understanding
inferredcites →https://doi.org/10.1109/tpami.2016.2554555openalex-snapshot
A Deep Matrix Factorization Method for Learning Attribute Representations
inferredcites →https://doi.org/10.1109/tsg.2013.2245926openalex-snapshot
Non-Intrusive Signature Extraction for Major Residential Loads
inferredcites →https://doi.org/10.1109/tsg.2013.2271282openalex-snapshot
An Empirical Investigation of V-I Trajectory Based Load Signatures for Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tsg.2013.2284760openalex-snapshot
A Novel Current Sensor for Home Energy Use Monitoring
inferredcites →https://doi.org/10.1109/tsg.2014.2321582openalex-snapshot
NilmDB: The Non-Intrusive Load Monitor Database
inferredcites →https://doi.org/10.1109/tsg.2015.2415456openalex-snapshot
A New Power Signature for Nonintrusive Appliance Load Monitoring
inferredcites →https://doi.org/10.1109/tsg.2015.2494592openalex-snapshot
Exploiting HMM Sparsity to Perform Online Real-Time Nonintrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tsg.2016.2584581openalex-snapshot
Toward Non-Intrusive Load Monitoring via Multi-Label Classification
inferredcites →https://doi.org/10.1109/tsp.2006.881199openalex-snapshot
$rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
inferredcites →https://doi.org/10.1137/080725891openalex-snapshot
The Split Bregman Method for L1-Regularized Problems
inferredcites →https://doi.org/10.1137/1.9781611972818.64openalex-snapshot
Unsupervised Disaggregation of Low Frequency Power Measurements
inferredcites →https://doi.org/10.1145/2208828.2208858openalex-snapshot
nPlug
inferredcites →https://doi.org/10.1184/r1/6603563openalex-snapshot
Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation
inferredcites →https://doi.org/10.1609/aaai.v26i1.8162openalex-snapshot
Non-Intrusive Load Monitoring Using Prior Models of General Appliance Types
inferredcites →https://doi.org/10.1609/aaai.v29i1.9249openalex-snapshot
Energy Disaggregation via Learning Powerlets and Sparse Coding
inferredcites →https://doi.org/10.48550/arxiv.1206.5882openalex-snapshot
Exact Recovery of Sparsely-Used Dictionaries
inferredcites →https://doi.org/10.48550/arxiv.1401.0579openalex-snapshot
More Algorithms for Provable Dictionary Learning
inferredcites →https://doi.org/10.48550/arxiv.1406.1943openalex-snapshot
Structured Dictionary Learning for Classification
inferredcites →https://doi.org/10.5555/1771592.1771608openalex-snapshot
At the flick of a switch: detecting and classifying unique electrical events on the residential power line

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Graph Regularized Deep Sparse Representation for Unsupervised Anomaly Detection
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Application of attention mechanism enhanced neural network in non-invasive load monitoring of industrial power data
inferred← citeshttps://doi.org/10.1186/s13634-020-0664-yopenalex-snapshot
Robust energy disaggregation using appliance-specific temporal contextual information
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Big data analytics in smart grids: a review
inferred← citeshttps://doi.org/10.2139/ssrn.7214158openalex-snapshot
Non-Intrusive Load Monitoring for Smart Grids: A Deployment-Oriented Review
inferred← citeshttps://doi.org/10.2174/9789815036244122010004openalex-snapshot
IOT-based Smart Energy Management in Buildings of Smart Cities
inferred← citeshttps://doi.org/10.23919/eusipco54536.2021.9616308openalex-snapshot
Low-Frequency Energy Disaggregation based on Active and Reactive Power Signatures
inferred← citeshttps://doi.org/10.3389/fenrg.2023.1140685openalex-snapshot
DRA-net: A new deep learning framwork for non-intrusive load disaggregation
inferred← citeshttps://doi.org/10.3390/app8040554openalex-snapshot
Low-Rate Non-Intrusive Load Disaggregation with Graph Shift Quadratic Form Constraint
inferred← citeshttps://doi.org/10.3390/app9173558openalex-snapshot
Non-Intrusive Load Disaggregation by Linear Classifier Group Considering Multi-Feature Integration
inferred← citeshttps://doi.org/10.3390/app9245363openalex-snapshot
Non-Intrusive Load Monitoring Using Current Shapelets
inferred← citeshttps://doi.org/10.3390/books978-3-03928-890-8openalex-snapshot
Artificial Intelligence for Smart and Sustainable Energy Systems and Applications
inferred← citeshttps://doi.org/10.3390/e22010071openalex-snapshot
Energy Disaggregation Using Elastic Matching Algorithms
inferred← citeshttps://doi.org/10.3390/electronics13193970openalex-snapshot
A Distributed Non-Intrusive Load Monitoring Method Using Karhunen–Loeve Feature Extraction and an Improved Deep Dictionary
inferred← citeshttps://doi.org/10.3390/en12112203openalex-snapshot
NILM Techniques for Intelligent Home Energy Management and Ambient Assisted Living: A Review
inferred← citeshttps://doi.org/10.3390/en13092148openalex-snapshot
Energy Disaggregation Using Two-Stage Fusion of Binary Device Detectors
inferred← citeshttps://doi.org/10.3390/en13092195openalex-snapshot
A Deep Recurrent Neural Network for Non-Intrusive Load Monitoring Based on Multi-Feature Input Space and Post-Processing
inferred← citeshttps://doi.org/10.3390/en13215629openalex-snapshot
Non-Intrusive Load Monitoring via Deep Learning Based User Model and Appliance Group Model
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Non-Intrusive Load Monitoring of Household Devices Using a Hybrid Deep Learning Model through Convex Hull-Based Data Selection
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A Novel Non-Intrusive Load Monitoring Algorithm for Unsupervised Disaggregation of Household Appliances
inferred← citeshttps://doi.org/10.3390/s20113289openalex-snapshot
The Power of Big Data and Data Analytics for AMI Data: A Case Study
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A Data Analytics/Big Data Framework for Advanced Metering Infrastructure Data
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An Enhanced Ensemble Approach for Non-Intrusive Energy Use Monitoring Based on Multidimensional Heterogeneity
inferred← citeshttps://doi.org/10.3390/s22155838openalex-snapshot
Semi-Supervised Domain Adaptation for Multi-Label Classification on Nonintrusive Load Monitoring
inferred← citeshttps://doi.org/10.3390/s22197200openalex-snapshot
2D Transformations of Energy Signals for Energy Disaggregation
inferred← citeshttps://doi.org/10.3390/su13020693openalex-snapshot
Event Matching Classification Method for Non-Intrusive Load Monitoring
inferred← citeshttps://doi.org/10.3390/su142214898openalex-snapshot
Non-Intrusive Load Monitoring of Residential Loads via Laplacian Eigenmaps and Hybrid Deep Learning Procedures
inferred← citeshttps://doi.org/10.4018/978-1-7998-2803-7.ch004openalex-snapshot
Cloud-Based IoT Architecture for Green Buildings
inferred← citeshttps://doi.org/10.4018/978-1-7998-9032-4.ch003openalex-snapshot
Cloud-Based IoT Architecture for Green Buildings
inferred← citeshttps://doi.org/10.46855/energy-proceedings-2204openalex-snapshot
Smart Grid Privacy Protection Strategy Based on Solar Energy and Rechargeable Battery
inferred← citeshttps://doi.org/10.47611/jsr.vi.905openalex-snapshot
Green Building – Energy Conservation using IoT
inferred← citeshttps://doi.org/10.48550/arxiv.1805.10635openalex-snapshot
IoT for Green Building Management
inferred← citeshttps://doi.org/10.48550/arxiv.1912.12130openalex-snapshot
Analysis Co-Sparse Coding for Energy Disaggregation
inferred← citeshttps://doi.org/10.48550/arxiv.2009.02656openalex-snapshot
A Novel Event-based Non-intrusive Load Monitoring Algorithm
inferred← citeshttps://doi.org/10.48550/arxiv.2110.05667openalex-snapshot
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks
inferred← citeshttps://doi.org/10.59275/j.melba.2024-1656openalex-snapshot
Alternative Learning Paradigms for Image Quality Transfer
inferred← citeshttps://doi.org/10.70675/95be8b63z79b0z4895za5edzdbe9916e8057openalex-snapshot
Functional time series modeling and application to representation and analysis of multi-site electric load curves for energy management
inferred← citeshttps://doi.org/10.7717/peerj-cs.3717openalex-snapshot
Non-intrusive load monitoring using Short-Time Fourier Transform (STFT)-based Local Phase Quantization (LPQ) features and hybrid deep–classical learning models
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.