Publications for Martin Renqiang Min

  • Accelerating deep neural network training with inconsistent stochastic gradient descent

    Neural Networks
    93 (2017) 219–229

    Linnan Wang, Yi Yang, Martin Renqiang Min, Srimat T. Chakradhar
    09/01/2017
  • Exemplar-Centered Supervised Shallow Parametric Data Embedding

    IJCAI 2017
    pp. 2749-2485, 2017

    Martin Renqiang Min, Hongyu Guo, Dongjin Song
    08/19/2017
  • A Context-aware Attention Network for Interactive Question Answering

    KDD 2017
    pp. 927-935, 2017

    Huayu Li, Martin Renqiang Min, Yong Ge, Asim Kadav
    08/13/2017
  • Adaptive Feature Abstraction for Translating Video to Language

    ICLR 2017
    pp. 1-4, 2017

    Yunchen Pu, Martin Renqiang Min, Zhe Gan, Lawrence Carin
    04/24/2017
  • Automated IT System Failure Prediction: A Deep Learning Approach

    Proceedings of the 2016 IEEE International Conference on Big Data
    pp. 1291-1300, 2016

    Ke Zhang, Jianwu Xu, Martin Renqiang Min, Guofei Jiang, Konstantinos Pelechrinis, Hui Zhang
    12/08/2016
  • Knowledge Based Factorized High Order Sparse Learning Models

    MLCB 2015
    pp.. 1-5, 2015

    Sanjay Purushotham, Martin Renqiang Min, Jay C.-C. Kuo, Mark Gerstein
    12/12/2015
  • Random Walk Distributed Dual Averaging Method For Decentralized Consensus Optimization

    NIPS Optimization Workshop (NIPS OPT'15)
    pp. 1-5, 2015

    Cun Mu, Asim Kadav, Erik Kruus, Martin Renqiang Min
    12/11/2015
  • High-Order Neural Networks and Kernel Methods for Peptide-MHC Binding Prediction

    Bioinformatics
    pp. 1-7, 2015

    Pavel P. Kuksa, Martin Renqiang Min, Rishabh Dugar, Mark Gerstein
    07/23/2015
  • High-Order Neural Networks and Kernel Methods for Peptide-MHC Binding Prediction

    NIPS 2014 Workshop on Machine Learning in Computational Biology
    pp. 1-4, 2014

    Pavel P. Kuksa, Martin Renqiang Min, Rishabh Dugar, Mark Gerstein
    12/13/2014
  • Ensemble Learning Based Sparse High-Order Boltzmann Machine for Unsupervised Feature Interaction Identification

    NIPS Workshop on Machine Learning in Computational Biology
    pp. 1-4, 2014

    Martin Renqiang Min, Xia Ning, Yanjun Qi, Chao Cheng, Anthony Bonner, Mark Gerstein
    12/13/2014
  • A Deep Learning Model for Structured Outputs with High-order Interaction

    NIPS workshop on Representation and Learning Methods for Complex Outputs
    pp. 1-6, 2014

    Hongyu Guo, Xiaodan Zhu, Martin Renqiang Min
    12/12/2014
  • Factorized Sparse Learning Models with Interpretable High Order Feature Interactions

    20th ACM SIGKDD Confeence on nowledge Discovery and Data Mining,
    NYC, New York

    Sanjay Purushotham, Martin Renqiang Min, C.-C. Jay Kuo, Rachal Ostroff
    08/24/2014
  • Deep Semantic Embedding

    Workshop on Semantic Matching in Information Retrieval (SMIR 2014), co-located with the 37th International ACM SIGIR Conference
    1204:pp. 46-52, Eds. J. Gonzalo, H. Li, A. Moschitti, J. Xu, Queensland, Australia

    Hao Wu, Martin Renqiang Min, Bing Bai
    07/11/2014
  • Interpretable Sparse High-Order Boltzmann Machines

    17th International Conference on Artificial Intelligence and Statistics (AISTATS 2014)
    JMLR: W&CP 33:pp. 614-622, Reykjavik, Iceland

    Martin Renqiang Min, Xia Ning, Chao Cheng, Mark Gerstein
    04/22/2014
  • An Integrated Approach to Blood-Based Cancer Diagnosis and Biomarker Discovery

    Pacific Symposium on Biocomputing (PSB 2014)
    19:87-98, 2014

    Martin Renqiang Min, Salim Chowdhury, Yanjun Qi, Alex Stewart, Rachel Ostroff
    01/06/2014
  • Interpretable Sparse High-Order Boltzmann Machines for Transcription Factor Interaction Identification

    2013 NIPS Workshop on Machine Learning in Computational Biology, Lake Tahoe, NV
    http://mlcb.org/

    Martin Renqiang Min, Xia Ning, Chao Cheng, Mark Gerstein
    12/10/2013