Mingjun Zhong

Orcid: 0000-0002-1525-1270

According to our database1, Mingjun Zhong authored at least 45 papers between 2004 and 2024.

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Bibliography

2024
Semantic Positive Pairs for Enhancing Visual Representation Learning of Instance Discrimination methods.
Trans. Mach. Learn. Res., 2024

A Survey of Pipeline Tools for Data Engineering.
CoRR, 2024

Capsule Network Projectors are Equivariant and Invariant Learners.
CoRR, 2024

LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations.
CoRR, 2024

Masked Capsule Autoencoders.
CoRR, 2024

2023
Lightweight deep learning methods for panoramic dental X-ray image segmentation.
Neural Comput. Appl., April, 2023

ProtoCaps: A Fast and Non-Iterative Capsule Network Routing Method.
Trans. Mach. Learn. Res., 2023

Nonintrusive Load Monitoring Based on Self-Supervised Learning.
IEEE Trans. Instrum. Meas., 2023

Semantic Positive Pairs for Enhancing Contrastive Instance Discrimination.
CoRR, 2023

Vanishing Activations: A Symptom of Deep Capsule Networks.
CoRR, 2023

2022
System operational reliability evaluation based on dynamic Bayesian network and XGBoost.
Reliab. Eng. Syst. Saf., 2022

Algorithms to Calculate the Most Reliable Maximum Flow in Content Delivery Network.
Comput. Syst. Sci. Eng., 2022

LightNILM: lightweight neural network methods for non-intrusive load monitoring.
Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, 2022

A Semantic Representation Scheme for Medical Dispute Judgment Documents Based on Elements Extraction.
Proceedings of the Artificial Intelligence and Security - 8th International Conference, 2022

Causal Effect Estimation Using Variational Information Bottleneck.
Proceedings of the Web Information Systems and Applications, 2022

2021
A discrete-time Bayesian network approach for reliability analysis of dynamic systems with common cause failures.
Reliab. Eng. Syst. Saf., 2021

A Top-K QoS-Optimal Service Composition Approach Based on Service Dependency Graph.
J. Organ. End User Comput., 2021

2020
Transfer Learning for Non-Intrusive Load Monitoring.
IEEE Trans. Smart Grid, 2020

Trust-Region Variational Inference with Gaussian Mixture Models.
J. Mach. Learn. Res., 2020

AREA: An adaptive reference-set based evolutionary algorithm for multiobjective optimisation.
Inf. Sci., 2020

Lightweight Non-Intrusive Load Monitoring Employing Pruned Sequence-to-Point Learning.
Proceedings of the NILM '20, 2020

2019
AREA: Adaptive Reference-set Based Evolutionary Algorithm for Multiobjective Optimisation.
CoRR, 2019

A demonstration of reproducible state-of-the-art energy disaggregation using NILMTK.
Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, 2019

Towards reproducible state-of-the-art energy disaggregation.
Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, 2019

Neural Control Variates for Monte Carlo Variance Reduction.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

2018
A Hyperplane Clustering Algorithm for Estimating the Mixing Matrix in Sparse Component Analysis.
Neural Process. Lett., 2018

Neural Control Variates for Variance Reduction.
CoRR, 2018

Efficient Gradient-Free Variational Inference using Policy Search.
Proceedings of the 35th International Conference on Machine Learning, 2018

Sequence-to-Point Learning With Neural Networks for Non-Intrusive Load Monitoring.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Pseudo-marginal Markov Chain Monte Carlo for Nonnegative Matrix Factorization.
Neural Process. Lett., 2017

2016
Sequence-to-point learning with neural networks for nonintrusive load monitoring.
CoRR, 2016

Classification of Normal/Abnormal Heart Sound Recordings based on Multi-Domain Features and Back Propagation Neural Network.
Proceedings of the Computing in Cardiology, CinC 2016, Vancouver, 2016

2015
Latent Bayesian melding for integrating individual and population models.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
A comparative evaluation of stochastic-based inference methods for Gaussian process models.
Mach. Learn., 2013

2012
Bayesian Analysis for miRNA and mRNA Interactions Using Expression Data
CoRR, 2012

A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices.
Proceedings of the 29th International Conference on Machine Learning, 2012

2009
Reversible Jump MCMC for Non-Negative Matrix Factorization.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

2008
Classifying EEG for brain computer interfaces using Gaussian processes.
Pattern Recognit. Lett., 2008

Scale-free network model under exogenous pressures.
Int. J. Model. Identif. Control., 2008

2007
A parametric density model for blind source separation.
Neural Process. Lett., 2007

2006
A variational method for learning sparse Bayesian regression.
Neurocomputing, 2006

Data Integration for Classification Problems Employing Gaussian Process Priors.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2004
Expectation-Maximization approaches to independent component analysis.
Neurocomputing, 2004

An EM algorithm for learning sparse and overcomplete representations.
Neurocomputing, 2004


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