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Journal Articles
- 2024
[j20]Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong:
Semantic Positive Pairs for Enhancing Visual Representation Learning of Instance Discrimination methods. Trans. Mach. Learn. Res. 2024 (2024)- 2023
- [j19]Songyue Lin, Xuejiang Hao, Yan Liu, Dong Yan, Jianwei Liu, Mingjun Zhong
:
Lightweight deep learning methods for panoramic dental X-ray image segmentation. Neural Comput. Appl. 35(11): 8295-8306 (2023) - [j18]Shuyi Chen, Bochao Zhao, Mingjun Zhong, Wenpeng Luan, Yixin Yu:
Nonintrusive Load Monitoring Based on Self-Supervised Learning. IEEE Trans. Instrum. Meas. 72: 1-13 (2023) - [j17]Miles Everett, Mingjun Zhong, Georgios Leontidis:
ProtoCaps: A Fast and Non-Iterative Capsule Network Routing Method. Trans. Mach. Learn. Res. 2023 (2023) - 2022
- [j16]Baili Zhang, Keke Ling, Pei Zhang, Zhao Zhang, Mingjun Zhong:
Algorithms to Calculate the Most Reliable Maximum Flow in Content Delivery Network. Comput. Syst. Sci. Eng. 41(2): 699-715 (2022) - [j15]Yongjin Guo, Hongdong Wang, Yu Guo, Mingjun Zhong, Qing Li, Chao Gao:
System operational reliability evaluation based on dynamic Bayesian network and XGBoost. Reliab. Eng. Syst. Saf. 225: 108622 (2022) - 2021
- [j14]Baili Zhang, Kejie Wen, Jianhua Lu, Mingjun Zhong:
A Top-K QoS-Optimal Service Composition Approach Based on Service Dependency Graph. J. Organ. End User Comput. 33(3): 50-68 (2021) - [j13]Yongjin Guo, Mingjun Zhong, Chao Gao, Hong Dong Wang, Xiaofeng Liang, Hong Yi:
A discrete-time Bayesian network approach for reliability analysis of dynamic systems with common cause failures. Reliab. Eng. Syst. Saf. 216: 108028 (2021) - 2020
- [j12]Shouyong Jiang, Hongru Li, Jinglei Guo, Mingjun Zhong, Shengxiang Yang, Marcus Kaiser, Natalio Krasnogor:
AREA: An adaptive reference-set based evolutionary algorithm for multiobjective optimisation. Inf. Sci. 515: 365-387 (2020) - [j11]Oleg Arenz, Mingjun Zhong, Gerhard Neumann:
Trust-Region Variational Inference with Gaussian Mixture Models. J. Mach. Learn. Res. 21: 163:1-163:60 (2020) - [j10]Michele D'Incecco, Stefano Squartini, Mingjun Zhong:
Transfer Learning for Non-Intrusive Load Monitoring. IEEE Trans. Smart Grid 11(2): 1419-1429 (2020) - 2018
- [j9]Xu Xu, Mingjun Zhong, Chonghui Guo:
A Hyperplane Clustering Algorithm for Estimating the Mixing Matrix in Sparse Component Analysis. Neural Process. Lett. 47(2): 475-490 (2018) - 2017
- [j8]Junfu Du, Mingjun Zhong:
Pseudo-marginal Markov Chain Monte Carlo for Nonnegative Matrix Factorization. Neural Process. Lett. 45(2): 553-562 (2017) - 2013
- [j7]Maurizio Filippone, Mingjun Zhong, Mark A. Girolami:
A comparative evaluation of stochastic-based inference methods for Gaussian process models. Mach. Learn. 93(1): 93-114 (2013) - 2008
- [j6]Qiang Guo, Jian-Guo Liu, Mingjun Zhong:
Scale-free network model under exogenous pressures. Int. J. Model. Identif. Control. 3(1): 79-82 (2008) - [j5]Mingjun Zhong, Fabien Lotte, Mark A. Girolami, Anatole Lécuyer:
Classifying EEG for brain computer interfaces using Gaussian processes. Pattern Recognit. Lett. 29(3): 354-359 (2008) - 2007
- [j4]Mingjun Zhong, Junfu Du:
A parametric density model for blind source separation. Neural Process. Lett. 25(3): 199-207 (2007) - 2006
- [j3]Mingjun Zhong:
A variational method for learning sparse Bayesian regression. Neurocomputing 69(16-18): 2351-2355 (2006) - 2004
- [j2]Mingjun Zhong, Huanwen Tang, Hongjun Chen, Yiyuan Tang:
An EM algorithm for learning sparse and overcomplete representations. Neurocomputing 57: 469-476 (2004) - [j1]Mingjun Zhong, Huanwen Tang, Yiyuan Tang:
Expectation-Maximization approaches to independent component analysis. Neurocomputing 61: 503-512 (2004)
Conference and Workshop Papers
- 2022
- [c15]Zhenyu Lu, Yurong Cheng, Mingjun Zhong, George Stoian, Ye Yuan, Guoren Wang:
Causal Effect Estimation Using Variational Information Bottleneck. WISA 2022: 288-296 - [c14]Siyao An, Tianhao Wang, Lirui Wang, Mingjun Zhong, Baili Zhang:
A Semantic Representation Scheme for Medical Dispute Judgment Documents Based on Elements Extraction. ICAIS (2) 2022: 400-414 - [c13]Zhenyu Lu, Yurong Cheng, Mingjun Zhong, Wenpeng Luan, Yuan Ye, Guoren Wang:
LightNILM: lightweight neural network methods for non-intrusive load monitoring. BuildSys@SenSys 2022: 383-387 - 2020
- [c12]Jack Barber, Heriberto Cuayáhuitl, Mingjun Zhong, Wenpeng Luan:
Lightweight Non-Intrusive Load Monitoring Employing Pruned Sequence-to-Point Learning. NILM@SenSys 2020: 11-15 - 2019
- [c11]Ruosi Wan, Mingjun Zhong, Haoyi Xiong, Zhanxing Zhu:
Neural Control Variates for Monte Carlo Variance Reduction. ECML/PKDD (2) 2019: 533-547 - [c10]Nipun Batra, Rithwik Kukunuri, Ayush Pandey, Raktim Malakar, Rajat Kumar, Odysseas Krystalakos, Mingjun Zhong, Paulo Meira, Oliver Parson:
Towards reproducible state-of-the-art energy disaggregation. BuildSys@SenSys 2019: 193-202 - [c9]Nipun Batra, Rithwik Kukunuri, Ayush Pandey, Raktim Malakar, Rajat Kumar, Odysseas Krystalakos, Mingjun Zhong, Paulo Meira, Oliver Parson:
A demonstration of reproducible state-of-the-art energy disaggregation using NILMTK. BuildSys@SenSys 2019: 358-359 - 2018
- [c8]Chaoyun Zhang, Mingjun Zhong, Zongzuo Wang, Nigel H. Goddard, Charles Sutton:
Sequence-to-Point Learning With Neural Networks for Non-Intrusive Load Monitoring. AAAI 2018: 2604-2611 - [c7]Oleg Arenz, Mingjun Zhong, Gerhard Neumann:
Efficient Gradient-Free Variational Inference using Policy Search. ICML 2018: 234-243 - 2016
- [c6]Hong Tang, Huaming Chen, Ting Li, Mingjun Zhong:
Classification of Normal/Abnormal Heart Sound Recordings based on Multi-Domain Features and Back Propagation Neural Network. CinC 2016 - 2015
- [c5]Mingjun Zhong, Nigel H. Goddard, Charles Sutton:
Latent Bayesian melding for integrating individual and population models. NIPS 2015: 3618-3626 - 2014
- [c4]Mingjun Zhong, Nigel H. Goddard, Charles Sutton:
Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation. NIPS 2014: 3590-3598 - 2012
- [c3]Mingjun Zhong, Mark A. Girolami:
A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices. ICML 2012 - 2009
- [c2]Mingjun Zhong, Mark A. Girolami:
Reversible Jump MCMC for Non-Negative Matrix Factorization. AISTATS 2009: 663-670 - 2006
- [c1]Mark A. Girolami, Mingjun Zhong:
Data Integration for Classification Problems Employing Gaussian Process Priors. NIPS 2006: 465-472
Informal and Other Publications
- 2024
- [i17]Miles Everett, Mingjun Zhong, Georgios Leontidis:
Masked Capsule Autoencoders. CoRR abs/2403.04724 (2024) - [i16]Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong:
LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations. CoRR abs/2403.06813 (2024) - [i15]Miles Everett, Aiden Durrant, Mingjun Zhong, Georgios Leontidis:
Capsule Network Projectors are Equivariant and Invariant Learners. CoRR abs/2405.14386 (2024) - [i14]Anthony Mbata, Yaji Sripada, Mingjun Zhong:
A Survey of Pipeline Tools for Data Engineering. CoRR abs/2406.08335 (2024) - 2023
- [i13]Miles Everett, Mingjun Zhong, Georgios Leontidis:
Vanishing Activations: A Symptom of Deep Capsule Networks. CoRR abs/2305.11178 (2023) - [i12]Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong:
Semantic Positive Pairs for Enhancing Contrastive Instance Discrimination. CoRR abs/2306.16122 (2023) - [i11]Miles Everett, Mingjun Zhong, Georgios Leontidis:
ProtoCaps: A Fast and Non-Iterative Capsule Network Routing Method. CoRR abs/2307.09944 (2023) - 2021
- [i10]Zhenyu Lu, Yurong Cheng, Mingjun Zhong, George Stoian, Ye Yuan, Guoren Wang:
Causal Effect Estimation using Variational Information Bottleneck. CoRR abs/2110.13705 (2021) - 2019
- [i9]Michele D'Incecco, Stefano Squartini, Mingjun Zhong:
Transfer Learning for Non-Intrusive Load Monitoring. CoRR abs/1902.08835 (2019) - [i8]Oleg Arenz, Mingjun Zhong, Gerhard Neumann:
Trust-Region Variational Inference with Gaussian Mixture Models. CoRR abs/1907.04710 (2019) - [i7]Shouyong Jiang, Hongru Li, Jinglei Guo, Mingjun Zhong, Shengxiang Yang, Marcus Kaiser, Natalio Krasnogor:
AREA: Adaptive Reference-set Based Evolutionary Algorithm for Multiobjective Optimisation. CoRR abs/1910.07491 (2019) - 2018
- [i6]Zhanxing Zhu, Ruosi Wan, Mingjun Zhong:
Neural Control Variates for Variance Reduction. CoRR abs/1806.00159 (2018) - [i5]Hong Tang, Huaming Chen, Ting Li, Mingjun Zhong:
Classification of normal/abnormal heart sound recordings based on multi-domain features and back propagation neural network. CoRR abs/1810.09253 (2018) - 2016
- [i4]Chaoyun Zhang, Mingjun Zhong, Zongzuo Wang, Nigel H. Goddard, Charles Sutton:
Sequence-to-point learning with neural networks for nonintrusive load monitoring. CoRR abs/1612.09106 (2016) - 2015
- [i3]Mingjun Zhong, Nigel H. Goddard, Charles Sutton:
Latent Bayesian melding for integrating individual and population models. CoRR abs/1510.09130 (2015) - 2012
- [i2]Mingjun Zhong, Mark A. Girolami:
A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices. CoRR abs/1206.4666 (2012) - [i1]Mingjun Zhong, Rong Liu, Bo Liu:
Bayesian Analysis for miRNA and mRNA Interactions Using Expression Data. CoRR abs/1210.3456 (2012)
Coauthor Index
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