Ning Chen

According to our database1, Ning Chen authored at least 35 papers between 2010 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2020
Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Ontology-based venous thromboembolism risk assessment model developing from medical records.
BMC Med. Inf. & Decision Making, 2019

Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness.
CoRR, 2019

Improving Adversarial Robustness via Promoting Ensemble Diversity.
Proceedings of the 36th International Conference on Machine Learning, 2019

Computer-aided Diagnosis of Ambulatory Electrocardiograms via ASRS: Active-Selection-Random-Selection.
Proceedings of the 2019 IEEE International Conference on Healthcare Informatics, 2019

DCMN: Double Core Memory Network for Patient Outcome Prediction with Multimodal Data.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

How Robust is Your Automatic Diagnosis Model?
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

DeepTriager: A Neural Attention Model for Emergency Triage with Electronic Health Records.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Bone Age Assessment by Deep Convolutional Neural Networks Combined with Clinical TW3-RUS.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2018
Dropout training for SVMs with data augmentation.
Frontiers Comput. Sci., 2018

Message Passing Stein Variational Gradient Descent.
Proceedings of the 35th International Conference on Machine Learning, 2018

Ontology-based Venous Thromboembolism Risk Factors Mining and Model Developing from Medical Records.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

2017
Predicting enhancers with deep convolutional neural networks.
BMC Bioinform., 2017

Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding.
Bioinform., 2017

DACE: a scalable DP-means algorithm for clustering extremely large sequence data.
Bioinform., 2017

Patient outcome prediction via convolutional neural networks based on multi-granularity medical concept embedding.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

Learning Attributes from the Crowdsourced Relative Labels.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
mLDM: A New Hierarchical Bayesian Statistical Model for Sparse Microbial Association Discovery.
Proceedings of the Research in Computational Molecular Biology - 20th Annual Conference, 2016

DeepEnhancer: Predicting enhancers by convolutional neural networks.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Discriminative Relational Topic Models.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Dropout Training for SVMs with Data Augmentation.
CoRR, 2015

2014
Learning Harmonium Models With Infinite Latent Features.
IEEE Trans. Neural Networks Learn. Syst., 2014

Bayesian inference with posterior regularization and applications to infinite latent SVMs.
J. Mach. Learn. Res., 2014

Gibbs max-margin topic models with data augmentation.
J. Mach. Learn. Res., 2014

Max-margin latent feature relational models for entity-attribute networks.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Dropout Training for Support Vector Machines.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Generalized Relational Topic Models with Data Augmentation.
Proceedings of the IJCAI 2013, 2013

Gibbs Max-Margin Topic Models with Fast Sampling Algorithms.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Large-Margin Predictive Latent Subspace Learning for Multiview Data Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., 2012

Bayesian Inference with Posterior Regularization and Infinite Latent Support Vector Machines
CoRR, 2012

2011
Infinite Latent SVM for Classification and Multi-task Learning.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Conditional topical coding: an efficient topic model conditioned on rich features.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Predictive Subspace Learning for Multi-view Data: a Large Margin Approach.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010


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