Ning Chen

Publication Activity (10 Years)

Years Active: 2008-2023
Publications (10 Years): 31

Top Topics

Relational Models

Outcome Prediction

Top Venues

Publications

Shouwei Ruan, Yinpeng Dong, Hang Su, Jianteng Peng, Ning Chen, Xingxing Wei
Towards Viewpoint-Invariant Visual Recognition via Adversarial Training. CoRR (2023)
Shouwei Ruan, Yinpeng Dong, Hang Su, Jianteng Peng, Ning Chen, Xingxing Wei
Towards Viewpoint-Invariant Visual Recognition via Adversarial Training. ICCV (2023)
Wenkai Li, Wenbo Hu, Ting Chen, Ning Chen, Cheng Feng
StackVAE-G: An efficient and interpretable model for time series anomaly detection. AI Open 3 (2022)
Chengyang Ying, Xinning Zhou, Hang Su, Dong Yan, Ning Chen, Jun Zhu
Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk. IJCAI (2022)
Yuqing Yang, Xin Wang, Kaikun Xie, Congmin Zhu, Ning Chen, Ting Chen
kLDM: Inferring Multiple Metagenomic Association Networks Based on the Variation of Environmental Factors. Genom. Proteom. Bioinform. 19 (5) (2021)
Yunsheng Zhang, Dong Yan, Bei Shi, Haobo Fu, Qiang Fu, Hang Su, Jun Zhu, Ning Chen
Combining Tree Search and Action Prediction for State-of-the-Art Performance in DouDiZhu. IJCAI (2021)
Ke Wang, Ning Chen, Ting Chen
Joint Medical Ontology Representation Learning for Healthcare Predictions. IJCNN (2020)
Tianyu Pang, Kun Xu, Yinpeng Dong, Chao Du, Ning Chen, Jun Zhu
Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness. ICLR (2020)
Ke Wang, Xuyan Chen, Ning Chen, Ting Chen
Automatic Emergency Diagnosis with Knowledge-Based Tree Decoding. IJCAI (2020)
Xuan Zhang, Guangyu Wang, Ning Chen, Ting Chen
Computer-aided Diagnosis of Ambulatory Electrocardiograms via ASRS: Active-Selection-Random-Selection. ICHI (2019)
Ke Wang, Guangyu Wang, Ning Chen, Ting Chen
How Robust is Your Automatic Diagnosis Model? BIBM (2019)
Ning Chen, Fuchun Sun, Linge Ding, Hongqiao Wang
An adaptive PNN-DS approach to classification using multi-sensor information fusion. Neural Comput. Appl. 31 (S-2) (2019)
Tianyu Pang, Kun Xu, Yinpeng Dong, Chao Du, Ning Chen, Jun Zhu
Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness. CoRR (2019)
Tianyu Pang, Kun Xu, Chao Du, Ning Chen, Jun Zhu
Improving Adversarial Robustness via Promoting Ensemble Diversity. ICML (2019)
Yujuan Feng, Zhenxing Xu, Lin Gan, Ning Chen, Bin Yu, Ting Chen, Fei Wang
DCMN: Double Core Memory Network for Patient Outcome Prediction with Multimodal Data. ICDM (2019)
Tianyu Pang, Kun Xu, Chao Du, Ning Chen, Jun Zhu
Improving Adversarial Robustness via Promoting Ensemble Diversity. CoRR (2019)
Yuqing Yang, Xin Wang, Yu Huang, Ning Chen, Juhong Shi, Ting Chen
Ontology-based venous thromboembolism risk assessment model developing from medical records. BMC Medical Informatics Decis. Mak. (4) (2019)
Xiaohong Liu, Guangyu Wang, Yiming Xu, Ning Chen, Ting Chen
Bone Age Assessment by Deep Convolutional Neural Networks Combined with Clinical TW3-RUS. BIBM (2019)
Guangyu Wang, Xiaohong Liu, Ken Xie, Ning Chen, Ting Chen
DeepTriager: A Neural Attention Model for Emergency Triage with Electronic Health Records. BIBM (2019)
Yuqing Yang, Xin Wang, Yu Huang, Ning Chen, Juhong Shi, Ting Chen
Ontology-based Venous Thromboembolism Risk Factors Mining and Model Developing from Medical Records. BIBM (2018)
Ning Chen, Jun Zhu, Jianfei Chen, Ting Chen
Dropout training for SVMs with data augmentation. Frontiers Comput. Sci. 12 (4) (2018)
Jingwei Zhuo, Chang Liu, Jiaxin Shi, Jun Zhu, Ning Chen, Bo Zhang
Message Passing Stein Variational Gradient Descent. ICML (2018)
Xu Min, Wanwen Zeng, Shengquan Chen, Ning Chen, Ting Chen, Rui Jiang
Predicting enhancers with deep convolutional neural networks. BMC Bioinform. 18 (S-13) (2017)
Xu Min, Wanwen Zeng, Ning Chen, Ting Chen, Rui Jiang
Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding. Bioinform. 33 (14) (2017)
Yujuan Feng, Xu Min, Ning Chen, Hu Chen, Xiaolei Xie, Haibo Wang, Ting Chen
Patient outcome prediction via convolutional neural networks based on multi-granularity medical concept embedding. BIBM (2017)
Linhao Jiang, Yichao Dong, Ning Chen, Ting Chen
DACE: a scalable DP-means algorithm for clustering extremely large sequence data. Bioinform. 33 (6) (2017)
Sai Zhang, Muxuan Liang, Zhongjun Zhou, Chen Zhang, Ning Chen, Ting Chen, Jianyang Zeng
Elastic restricted Boltzmann machines for cancer data analysis. Quant. Biol. 5 (2) (2017)
Tian Tian, Ning Chen, Jun Zhu
Learning Attributes from the Crowdsourced Relative Labels. AAAI (2017)
Yuqing Yang, Ning Chen, Ting Chen
mLDM: A New Hierarchical Bayesian Statistical Model for Sparse Microbial Association Discovery. RECOMB (2016)
Bei Chen, Ning Chen, Jun Zhu, Jiaming Song, Bo Zhang
Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation. AAAI (2016)
Xu Min, Ning Chen, Ting Chen, Rui Jiang
DeepEnhancer: Predicting enhancers by convolutional neural networks. BIBM (2016)
Bei Chen, Ning Chen, Jun Zhu, Jiaming Song, Bo Zhang
Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation. CoRR (2015)
Ning Chen, Jun Zhu, Jianfei Chen, Ting Chen
Dropout Training for SVMs with Data Augmentation. CoRR (2015)
Ning Chen, Jun Zhu, Fei Xia, Bo Zhang
Discriminative Relational Topic Models. IEEE Trans. Pattern Anal. Mach. Intell. 37 (5) (2015)
Fei Xia, Ning Chen, Jun Zhu, Aonan Zhang, Xiaoming Jin
Max-margin latent feature relational models for entity-attribute networks. IJCNN (2014)
Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang
Dropout Training for Support Vector Machines. AAAI (2014)
Jun Zhu, Ning Chen, Eric P. Xing
Bayesian inference with posterior regularization and applications to infinite latent SVMs. J. Mach. Learn. Res. 15 (1) (2014)
Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang
Dropout Training for Support Vector Machines. CoRR (2014)
Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang
Gibbs max-margin topic models with data augmentation. J. Mach. Learn. Res. 15 (1) (2014)
Ning Chen, Jun Zhu, Fuchun Sun, Bo Zhang
Learning Harmonium Models With Infinite Latent Features. IEEE Trans. Neural Networks Learn. Syst. 25 (3) (2014)
Ning Chen, Jun Zhu, Fei Xia, Bo Zhang
Discriminative Relational Topic Models. CoRR (2013)
Ning Chen, Jun Zhu, Fei Xia, Bo Zhang
Generalized Relational Topic Models with Data Augmentation. IJCAI (2013)
Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang
Gibbs Max-margin Topic Models with Data Augmentation. CoRR (2013)
Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang
Gibbs Max-Margin Topic Models with Fast Sampling Algorithms. ICML (1) (2013)
Ning Chen, Jun Zhu, Fuchun Sun, Eric P. Xing
Large-Margin Predictive Latent Subspace Learning for Multiview Data Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 34 (12) (2012)
Jun Zhu, Ning Chen, Eric P. Xing
Bayesian Inference with Posterior Regularization and Infinite Latent Support Vector Machines CoRR (2012)
Jun Zhu, Ning Chen, Eric P. Xing
Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines. ICML (2011)
Jun Zhu, Ning Chen, Eric P. Xing
Infinite Latent SVM for Classification and Multi-task Learning. NIPS (2011)
Jun Zhu, Ni Lao, Ning Chen, Eric P. Xing
Conditional topical coding: an efficient topic model conditioned on rich features. KDD (2011)
Ning Chen, Jun Zhu, Eric P. Xing
Predictive Subspace Learning for Multi-view Data: a Large Margin Approach. NIPS (2010)
Hongqiao Wang, Fuchun Sun, Yan-Ning Cai, Linge Ding, Ning Chen
An unbiased LSSVM model for classification and regression. Soft Comput. 14 (2) (2010)
Ning Chen, Fuchun Sun, Linge Ding, Hongqiao Wang
An adaptive PNN-DS approach to classification using multi-sensor information fusion. Neural Comput. Appl. 18 (5) (2009)
Linge Ding, Fuchun Sun, Hongqiao Wang, Ning Chen
A Sparse Sampling Method for Classification Based on Likelihood Factor. ISNN (2) (2008)