顾彬 - 南京信息工程大学 - 计算机与软件学院

个人简介

学习经历 2001-2005 南京航空航天大学，计算机科学与技术，本科 2005-2007 南京航空航天大学，计算机科学与技术，硕士 2007-2011 南京航空航天大学，计算机科学与技术，博士出国经历 2013.1-2015.1：加拿大西安大略大学医学生物物理学系数字图像组，以及计算机科学系Charles X. Ling教授数据挖掘以及商业智能组做博士后研究 2016.8-2017.8：美国德克萨斯州立大学Arlington分校，Heng Huang组做博后 2017.9-2018.7：美国匹兹堡大学，Heng Huang组做博后工作经历： 2010-至今：南京信息工程大学计算机与软件学院，教授

研究领域

主要是机器学习、商业智能分析以及医疗图像分析，具体包括机器学习中的优化方法（支持向量机的增量式学习、大数据学习、模型选择、稀疏化学习），代价敏感学习、引入先验知识的学习以及在商业智能以及医疗图像分析中的应用

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

Wanli Shi,Xiang Li, Bin Gu. Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization. AAAI 2020.(accepted) Zhou Zhai,Xiang Li, Bin Gu. Safe Sample Screening for Robust Support Vector Machine. AAAI 2020.(accepted) Runxue Bao, Bin Gu, Heng Huang. Efficient Approximate Solution Path Algorithm for Order Weight L_1-Norm with Accuracy Guarantee. ICDM 2019. Bin Gu, Xiang Geng, Xiang Li, Guansheng Zheng. Efficient Inexact Proximal Gradient Algorithms for Structured Sparsity-Inducing Norm. Neural Networks. (accepted) (SCI一区) Bin Gu, Wenhan Xian, Heng Huang.Asynchronous Stochastic Frank-Wolfe Algorithms for Non-convex Optimization.IJCAI 2019.(CCF A类) Xiang Geng, Bin Gu, Xiang Li, Wanli Shi, Guansheng Zheng, Heng Huang. Scalable Semi-Supervised SVM via Triply Stochastic Gradients.IJCAI 2019.(CCF A类) Wanli Shi, Bin Gu, Xiang Li, Xiang Geng, Heng Huang. Quadruply Stochastic Gradients for Large-Scale Nonlinear Semi-Supervised AUC Optimization. IJCAI 2019.(CCF A类) Shuyang Yu, Bin Gu, Kunpeng Ning, Haiyan Chen, Jian Pei and Heng Huang. Tackle Balancing Constraint for Incremental Semi-Supervised Support Vector Learning. KDD 2019.(CCF A类) Bin Gu, Yingying Shan，Xin Quan, Guansheng Zheng. Accelerating Sequential Minimal Optimization via Stochastic Sub-Gradient Descent. IEEE Transactions on Cybernetics. (accepted)(SCI一区) Feihu Huang,Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang. Faster Gradient-Free Proximal Stochastic Methods forNonconvex Nonsmooth Optimization. AAAI 2019. (CCF A类) Bin Gu, Zhouyuan Huo, Heng Huang. Scalable and Efficient Pairwise Learning to Achieve Statistical Accuracy. AAAI 2019. (CCF A类) Zhouyuan Huo, Bin Gu, Heng Huang Training Neural Networks Using Features Replay. NIPS 2018. (CCF A类) Bin Gu, Xin Quan, Yunhua Gu, Victor S. Sheng, Guansheng Zheng. Chunk Incremental Learning for Cost-Sensitive Hinge Loss Support Vector Machine. Pattern Recognition. (accepted) (SCI二区) Bin Gu, Zhouyuan Huo, Heng Huang. Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines. ICML 2018. (CCF A类) Zhouyuan Huo, Bin Gu, Qian Yang, Heng Huang. Decoupled Parallel Backpropagation with Convergence Guarantee. ICML 2018. (CCF A类) Bin Gu, Xiao-Tong Yuan, Songcan Chen, Heng Huang. New Incremental Learning Algorithm for Semi-Supervised Support Vector Machine. KDD 2018. (CCF A类) Bin Gu, Xingwang Ju, Xiang Li, Guansheng Zheng, Heng Huang. Faster Training Algorithms for Structured Sparsity-Inducing Norm. IJCAI 2018 . (accepted) (CCF A类) Bin Gu, Yingying Shan, Xiang Geng, Guansheng Zheng, Heng Huang. Accelerated Asynchronous Greedy Coordinate Descent Algorithm for SVMs. IJCAI 2018 . (accepted) (CCF A类) Bin Gu, Zhouyuan Huo, Heng Huang. Asynchronous Doubly Stochastic Group Regularized Learning. AISTATS 2018. (accepted) Bin Gu, Victor S. Sheng. A Solution Path Algorithm for General Parametric Quadratic Programming Problem. IEEE Transactions on Neural Networks and Learning Systems.(accepted) (SCI一区)