A Sparse Sampling Method for Classification Based on Likelihood Factor. - Linge Ding; Fuchun Sun 001; Hongqiao Wang; Ning Chen 002 (ISNN (2), 2008)

Predictive Subspace Learning for Multi-view Data: a Large Margin Approach. - Ning Chen 002; Jun Zhu 001; Eric P. Xing (NIPS, 2010)

An unbiased LSSVM model for classification and regression. - Hongqiao Wang; Fuchun Sun 001; Yan-Ning Cai; Linge Ding; Ning Chen 002 (Soft Comput., 2010)

Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines. - Jun Zhu 001; Ning Chen 002; Eric P. Xing (ICML, 2011)

Conditional topical coding: an efficient topic model conditioned on rich features. - Jun Zhu 001; Ni Lao; Ning Chen 002; Eric P. Xing (KDD, 2011)

Infinite Latent SVM for Classification and Multi-task Learning. - Jun Zhu 001; Ning Chen 002; Eric P. Xing (NIPS, 2011)

Bayesian Inference with Posterior Regularization and Infinite Latent Support Vector Machines - Jun Zhu 001; Ning Chen 002; Eric P. Xing (CoRR, 2012)

Large-Margin Predictive Latent Subspace Learning for Multiview Data Analysis. - Ning Chen 002; Jun Zhu 001; Fuchun Sun 001; Eric P. Xing (IEEE Trans. Pattern Anal. Mach. Intell., 2012)

Gibbs Max-Margin Topic Models with Fast Sampling Algorithms. - Jun Zhu 001; Ning Chen 002; Hugh Perkins; Bo Zhang 010 (ICML (1), 2013)

Generalized Relational Topic Models with Data Augmentation. - Ning Chen 002; Jun Zhu 001; Fei Xia 005; Bo Zhang 010 (IJCAI, 2013)

Dropout Training for Support Vector Machines. - Ning Chen 002; Jun Zhu 001; Jianfei Chen 001; Bo Zhang 010 (AAAI, 2014)

Max-margin latent feature relational models for entity-attribute networks. - Fei Xia 005; Ning Chen 002; Jun Zhu 001; Aonan Zhang; Xiaoming Jin (IJCNN, 2014)

Gibbs max-margin topic models with data augmentation. - Jun Zhu 001; Ning Chen 002; Hugh Perkins; Bo Zhang 010 (J. Mach. Learn. Res., 2014)

Bayesian inference with posterior regularization and applications to infinite latent SVMs. - Jun Zhu 001; Ning Chen 002; Eric P. Xing (J. Mach. Learn. Res., 2014)

Learning Harmonium Models With Infinite Latent Features. - Ning Chen 002; Jun Zhu 001; Fuchun Sun 001; Bo Zhang 010 (IEEE Trans. Neural Networks Learn. Syst., 2014)

Discriminative Relational Topic Models. - Ning Chen 002; Jun Zhu 001; Fei Xia 005; Bo Zhang 010 (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation. - Bei Chen; Ning Chen 002; Jun Zhu 001; Jiaming Song; Bo Zhang 010 (AAAI, 2016)

DeepEnhancer: Predicting enhancers by convolutional neural networks. - Xu Min; Ning Chen 002; Ting Chen 006; Rui Jiang 001 (BIBM, 2016)

mLDM: A New Hierarchical Bayesian Statistical Model for Sparse Microbial Association Discovery. - Yuqing Yang; Ning Chen 002; Ting Chen 006 (RECOMB, 2016)

Learning Attributes from the Crowdsourced Relative Labels. - Tian Tian 001; Ning Chen 002; Jun Zhu 001 (AAAI, 2017)

Patient outcome prediction via convolutional neural networks based on multi-granularity medical concept embedding. - Yujuan Feng; Xu Min; Ning Chen 002; Hu Chen; Xiaolei Xie; Haibo Wang; Ting Chen 006 (BIBM, 2017)

DACE: a scalable DP-means algorithm for clustering extremely large sequence data. - Linhao Jiang; Yichao Dong; Ning Chen 002; Ting Chen 006 (Bioinform., 2017)

Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding. - Xu Min; Wanwen Zeng; Ning Chen 002; Ting Chen 006; Rui Jiang 001 (Bioinform., 2017)

Predicting enhancers with deep convolutional neural networks. - Xu Min; Wanwen Zeng; Shengquan Chen; Ning Chen 002; Ting Chen 006; Rui Jiang 001 (BMC Bioinform., 2017)

Elastic restricted Boltzmann machines for cancer data analysis. - Sai Zhang; Muxuan Liang; Zhongjun Zhou; Chen Zhang; Ning Chen 002; Ting Chen 006; Jianyang Zeng 001 (Quant. Biol., 2017)

Ontology-based Venous Thromboembolism Risk Factors Mining and Model Developing from Medical Records. - Yuqing Yang; Xin Wang; Yu Huang; Ning Chen 002; Juhong Shi; Ting Chen 006 (BIBM, 2018)

Message Passing Stein Variational Gradient Descent. - Jingwei Zhuo; Chang Liu 030; Jiaxin Shi; Jun Zhu 001; Ning Chen 002; Bo Zhang 010 (ICML, 2018)

Dropout training for SVMs with data augmentation. - Ning Chen 002; Jun Zhu 001; Jianfei Chen 001; Ting Chen 006 (Frontiers Comput. Sci., 2018)

Bone Age Assessment by Deep Convolutional Neural Networks Combined with Clinical TW3-RUS. - Xiaohong Liu 007; Guangyu Wang; Yiming Xu; Ning Chen 002; Ting Chen 006 (BIBM, 2019)

DeepTriager: A Neural Attention Model for Emergency Triage with Electronic Health Records. - Guangyu Wang; Xiaohong Liu 007; Ken Xie; Ning Chen 002; Ting Chen 006 (BIBM, 2019)

How Robust is Your Automatic Diagnosis Model? - Ke Wang; Guangyu Wang; Ning Chen 002; Ting Chen 006 (BIBM, 2019)

DCMN: Double Core Memory Network for Patient Outcome Prediction with Multimodal Data. - Yujuan Feng; Zhenxing Xu; Lin Gan; Ning Chen 002; Bin Yu; Ting Chen 006; Fei Wang 001 (ICDM, 2019)

Computer-aided Diagnosis of Ambulatory Electrocardiograms via ASRS: Active-Selection-Random-Selection. - Xuan Zhang; Guangyu Wang; Ning Chen 002; Ting Chen 006 (ICHI, 2019)

Improving Adversarial Robustness via Promoting Ensemble Diversity. - Tianyu Pang; Kun Xu 004; Chao Du; Ning Chen 002; Jun Zhu 001 (ICML, 2019)

Transferable Adversarial Attacks for Image and Video Object Detection. - Xingxing Wei 001; Siyuan Liang; Ning Chen 002; Xiaochun Cao (IJCAI, 2019)

Ontology-based venous thromboembolism risk assessment model developing from medical records. - Yuqing Yang; Xin Wang; Yu Huang; Ning Chen 002; Juhong Shi; Ting Chen 006 (BMC Medical Informatics Decis. Mak., 2019)

An adaptive PNN-DS approach to classification using multi-sensor information fusion. - Ning Chen 002; Fuchun Sun 001; Linge Ding; Hongqiao Wang (Neural Comput. Appl., 2019)

Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness. - Tianyu Pang; Kun Xu 004; Yinpeng Dong; Chao Du; Ning Chen 002; Jun Zhu 001 (ICLR, 2020)

Automatic Emergency Diagnosis with Knowledge-Based Tree Decoding. - Ke Wang; Xuyan Chen; Ning Chen 002; Ting Chen 006 (IJCAI, 2020)

Joint Medical Ontology Representation Learning for Healthcare Predictions. - Ke Wang; Ning Chen 002; Ting Chen 006 (IJCNN, 2020)

Two Birds with One Stone: Series Saliency for Accurate and Interpretable Multivariate Time Series Forecasting. - Qingyi Pan; Wenbo Hu 001; Ning Chen 002 (IJCAI, 2021)

Combining Tree Search and Action Prediction for State-of-the-Art Performance in DouDiZhu. - Yunsheng Zhang; Dong Yan; Bei Shi; Haobo Fu; Qiang Fu 016; Hang Su 006; Jun Zhu 001; Ning Chen 002 (IJCAI, 2021)

Stacking VAE with Graph Neural Networks for Effective and Interpretable Time Series Anomaly Detection. - Wenkai Li; Wenbo Hu 001; Ning Chen 002; Cheng Feng 004 (CoRR, 2021)

redPATH: Reconstructing the Pseudo Development Time of Cell Lineages in Single-cell RNA-seq Data and Applications in Cancer. - Kaikun Xie; Zehua Liu; Ning Chen 002; Ting Chen 006 (Genom. Proteom. Bioinform., 2021)

kLDM: Inferring Multiple Metagenomic Association Networks Based on the Variation of Environmental Factors. - Yuqing Yang; Xin Wang; Kaikun Xie; Congmin Zhu; Ning Chen 002; Ting Chen 006 (Genom. Proteom. Bioinform., 2021)

Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk. - Chengyang Ying; Xinning Zhou; Hang Su 006; Dong Yan; Ning Chen 002; Jun Zhu 001 (IJCAI, 2022)

StackVAE-G: An efficient and interpretable model for time series anomaly detection. - Wenkai Li; Wenbo Hu 001; Ting Chen 006; Ning Chen 002; Cheng Feng 004 (AI Open, 2022)

Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition. - Xiao Yang; Chang Liu 077; Longlong Xu; Yikai Wang 001; Yinpeng Dong; Ning Chen 002; Hang Su 006; Jun Zhu 001 (CVPR, 2023)

Towards Viewpoint-Invariant Visual Recognition via Adversarial Training. - Shouwei Ruan; Yinpeng Dong; Hang Su 006; Jianteng Peng; Ning Chen 002; Xingxing Wei 001 (ICCV, 2023)

Improving Viewpoint Robustness for Visual Recognition via Adversarial Training. - Shouwei Ruan; Yinpeng Dong; Hang Su 006; Jianteng Peng; Ning Chen 002; Xingxing Wei 001 (CoRR, 2023)