Bin Gu

According to our database, Bin Gu authored at least 128 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Messages are Never Propagated Alone: Collaborative Hypergraph Neural Network for Time-Series Forecasting.

Nan Yin, Li Shen, Huan Xiong, Bin Gu, Chong Chen, Xian-Sheng Hua, Siwei Liu, Xiao Luo

IEEE Trans. Pattern Anal. Mach. Intell., April, 2024

Kernel Path for Semisupervised Support Vector Machine.

Zhou Zhai, Heng Huang, Bin Gu

IEEE Trans. Neural Networks Learn. Syst., February, 2024

FTBC: Forward Temporal Bias Correction for Optimizing ANN-SNN Conversion.

Xiaofeng Wu, Velibor Bojkovic, Bin Gu, Kun Suo, Kai Zou

CoRR, 2024

Federated Causal Discovery from Heterogeneous Data.

Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang

CoRR, 2024

Dynamic Spiking Graph Neural Networks.

Nan Yin, Mengzhu Wang, Zhenghan Chen, Giulia De Masi, Huan Xiong, Bin Gu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery.

William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Enhancing Training of Spiking Neural Network with Stochastic Latency.

Srinivas Anumasa, Bhaskar Mukhoty, Velibor Bojkovic, Giulia De Masi, Huan Xiong, Bin Gu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging.

Hilal AlQuabeh, William de Vazelhes, Bin Gu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Kernel Error Path Algorithm.

Ziran Xiong, Charles X. Ling, Bin Gu

IEEE Trans. Neural Networks Learn. Syst., November, 2023

A new large-scale learning algorithm for generalized additive models.

Bin Gu, Chenkang Zhang, Zhouyuan Huo, Heng Huang

Mach. Learn., September, 2023

Kernel Path for ν-Support Vector Classification.

Bin Gu, Ziran Xiong, Xiang Li, Zhou Zhai, Guansheng Zheng

IEEE Trans. Neural Networks Learn. Syst., 2023

Incremental learning for transductive support vector machine.

Haiyan Chen, Ying Yu, Yizhen Jia, Bin Gu

Pattern Recognit., 2023

Rethinking the Instruction Quality: LIFT is What You Need.

Yang Xu, Yongqiang Yao, Yufan Huang, Mengnan Qi, Maoquan Wang, Bin Gu, Neel Sundaresan

CoRR, 2023

Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory.

Hilal AlQuabeh, Bhaskar Mukhoty, Bin Gu

CoRR, 2023

Secure and Fast Asynchronous Vertical Federated Learning via Cascaded Hybrid Optimization.

Ganyu Wang, Qingsong Zhang, Li Xiang, Boyu Wang, Bin Gu, Charles Ling

CoRR, 2023

Advancing Counterfactual Inference through Quantile Regression.

Shaoan Xie, Biwei Huang, Bin Gu, Tongliang Liu, Kun Zhang

CoRR, 2023

Energy Efficient Training of SNN using Local Zeroth Order Method.

Bhaskar Mukhoty, Velibor Bojkovic, William de Vazelhes, Giulia De Masi, Huan Xiong, Bin Gu

CoRR, 2023

Accelerated On-Device Forward Neural Network Training with Module-Wise Descending Asynchronism.

Xiaohan Zhao, Hualin Zhang, Zhouyuan Huo, Bin Gu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning.

Ganyu Wang, Bin Gu, Qingsong Zhang, Xiang Li, Boyu Wang, Charles X. Ling

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Direct Training of SNN using Local Zeroth Order Method.

Bhaskar Mukhoty, Velibor Bojkovic, William de Vazelhes, Xiaohan Zhao, Giulia De Masi, Huan Xiong, Bin Gu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization.

Jun Chen, Hong Chen, Bin Gu, Hao Deng

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Doubly Robust AUC Optimization against Noisy and Adversarial Samples.

Chenkang Zhang, Wanli Shi, Lei Luo, Bin Gu

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Self-Adaptive Perturbation Radii for Adversarial Training.

Huimin Wu, Wanli Shi, Chenkang Zhang, Bin Gu

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

A Unified Optimization Framework of ANN-SNN Conversion: Towards Optimal Mapping from Activation Values to Firing Rates.

Haiyan Jiang, Srinivas Anumasa, Giulia De Masi, Huan Xiong, Bin Gu

Proceedings of the International Conference on Machine Learning, 2023

Faster Gradient-Free Methods for Escaping Saddle Points.

Hualin Zhang, Bin Gu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

SUT: Active Defects Probing for Transcompiler Models.

Mengnan Qi, Yufan Huang, Maoquan Wang, Yongqiang Yao, Zihan Liu, Bin Gu, Colin B. Clement, Neel Sundaresan

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Program Translation via Code Distillation.

Yufan Huang, Mengnan Qi, Yongqiang Yao, Maoquan Wang, Bin Gu, Colin B. Clement, Neel Sundaresan

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network.

Hongchang Gao, Bin Gu, My T. Thai

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Denoising Multi-Similarity Formulation: A Self-Paced Curriculum-Driven Approach for Robust Metric Learning.

Chenkang Zhang, Lei Luo, Bin Gu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Faster Fair Machine via Transferring Fairness Constraints to Virtual Samples.

Zhou Zhai, Lei Luo, Heng Huang, Bin Gu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Stability-Based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning.

Jiahuan Wang, Jun Chen, Hong Chen, Bin Gu, Weifu Li, Xin Tang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

When Online Learning Meets ODE: Learning without Forgetting on Variable Feature Space.

Diyang Li, Bin Gu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

On the Stability and Generalization of Triplet Learning.

Jun Chen, Hong Chen, Xue Jiang, Bin Gu, Weifu Li, Tieliang Gong, Feng Zheng

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Privacy-Preserving Asynchronous Vertical Federated Learning Algorithms for Multiparty Collaborative Learning.

Bin Gu, An Xu, Zhouyuan Huo, Cheng Deng, Heng Huang

IEEE Trans. Neural Networks Learn. Syst., 2022

Scaling Up Generalized Kernel Methods.

Bin Gu, Zhiyuan Dang, Zhouyuan Huo, Cheng Deng, Heng Huang

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Large-Scale Nonlinear AUC Maximization via Triply Stochastic Gradients.

Zhiyuan Dang, Xiang Li, Bin Gu, Cheng Deng, Heng Huang

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Incremental learning algorithm for large-scale semi-supervised ordinal regression.

Haiyan Chen, Yizhen Jia, Jiaming Ge, Bin Gu

Neural Networks, 2022

Stochastic Bilevel Distributed Optimization over a Network.

Hongchang Gao, Bin Gu, My T. Thai

CoRR, 2022

Learning to Control under Time-Varying Environment.

Yuzhen Han, Ruben Solozabal, Jing Dong, Xingyu Zhou, Martin Takác, Bin Gu

CoRR, 2022

Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients.

Hualin Zhang, Huan Xiong, Bin Gu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity.

William de Vazelhes, Hualin Zhang, Huimin Wu, Xiaotong Yuan, Bin Gu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

GAGA: Deciphering Age-path of Generalized Self-paced Regularizer.

Xingyu Qu, Diyang Li, Xiaohan Zhao, Bin Gu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

End-to-End Semi-Supervised Ordinal Regression AUC Maximization with Convolutional Kernel Networks.

Ziran Xiong, Wanli Shi, Bin Gu

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Gradient-Free Method for Heavily Constrained Nonconvex Optimization.

Wanli Shi, Hongchang Gao, Bin Gu

Proceedings of the International Conference on Machine Learning, 2022

The power of first-order smooth optimization for black-box non-smooth problems.

Alexander V. Gasnikov, Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takác, Pavel E. Dvurechensky, Bin Gu

Proceedings of the International Conference on Machine Learning, 2022

Efficient Semi-Supervised Adversarial Training without Guessing Labels.

Huimin Wu, William de Vazelhes, Bin Gu

Proceedings of the IEEE International Conference on Data Mining, 2022

Towards Practical Large Scale Non-Linear Semi-Supervised Learning with Balancing Constraints.

Zhengqing Gao, Huimin Wu, Martin Takác, Bin Gu

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification.

Runxue Bao, Bin Gu, Heng Huang

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Towards Fairer Classifier via True Fairness Score Path.

Bin Gu, Zhou Zhai, Xiang Li, Heng Huang

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Chunk Dynamic Updating for Group Lasso with ODEs.

Diyang Li, Bin Gu

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse.

Junyi Li, Bin Gu, Heng Huang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Balanced Self-Paced Learning for AUC Maximization.

Bin Gu, Chenkang Zhang, Huan Xiong, Heng Huang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Efficient Active Learning by Querying Discriminative and Representative Samples and Fully Exploiting Unlabeled Data.

Bin Gu, Zhou Zhai, Cheng Deng, Heng Huang

IEEE Trans. Neural Networks Learn. Syst., 2021

Scalable Kernel Ordinal Regression via Doubly Stochastic Gradients.

Bin Gu, Xiang Geng, Xiang Li, Wanli Shi, Guansheng Zheng, Cheng Deng, Heng Huang

IEEE Trans. Neural Networks Learn. Syst., 2021

Accelerating Sequential Minimal Optimization via Stochastic Subgradient Descent.

Bin Gu, Yingying Shan, Xin Quan, Guansheng Zheng

IEEE Trans. Cybern., 2021

A kernel path algorithm for general parametric quadratic programming problem.

Bin Gu, Ziran Xiong, Shuyang Yu, Guansheng Zheng

Pattern Recognit., 2021

Generalized error path algorithm.

Bin Gu, Charles X. Ling

Pattern Recognit., 2021

Solving large-scale support vector ordinal regression with asynchronous parallel coordinate descent algorithms.

Bin Gu, Xiang Geng, Wanli Shi, Yingying Shan, Yufang Huang, Zhijie Wang, Guansheng Zheng

Pattern Recognit., 2021

Triply stochastic gradient method for large-scale nonlinear similar unlabeled classification.

Wanli Shi, Bin Gu, Xiang Li, Cheng Deng, Heng Huang

Mach. Learn., 2021

Black-Box Reductions for Zeroth-Order Gradient Algorithms to Achieve Lower Query Complexity.

Bin Gu, Xiyuan Wei, Shangqian Gao, Ziran Xiong, Cheng Deng, Heng Huang

J. Mach. Learn. Res., 2021

An Accelerated Variance-Reduced Conditional Gradient Sliding Algorithm for First-order and Zeroth-order Optimization.

Xiyuan Wei, Bin Gu, Heng Huang

CoRR, 2021

Learning Sampling Policy for Faster Derivative Free Optimization.

Zhou Zhai, Bin Gu, Heng Huang

CoRR, 2021

Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm.

Bin Gu, Guodong Liu, Yanfu Zhang, Xiang Geng, Heng Huang

CoRR, 2021

AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization.

Qingsong Zhang, Bin Gu, Cheng Deng, Songxiang Gu, Liefeng Bo, Jian Pei, Heng Huang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Finding Age Path of Self-Paced Learning.

Bin Gu, Zhou Zhai, Xiang Li, Heng Huang

Proceedings of the IEEE International Conference on Data Mining, 2021

Desirable Companion for Vertical Federated Learning: New Zeroth-Order Gradient Based Algorithm.

Qingsong Zhang, Bin Gu, Zhiyuan Dang, Cheng Deng, Heng Huang

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating.

Qingsong Zhang, Bin Gu, Cheng Deng, Heng Huang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients.

Huimin Wu, Zhengmian Hu, Bin Gu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Improved Penalty Method via Doubly Stochastic Gradients for Bilevel Hyperparameter Optimization.

Wanli Shi, Bin Gu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Large Batch Optimization for Deep Learning Using New Complete Layer-Wise Adaptive Rate Scaling.

Zhouyuan Huo, Bin Gu, Heng Huang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Large-Scale Kernel Method for Vertical Federated Learning.

Zhiyuan Dang, Bin Gu, Heng Huang

Proceedings of the Federated Learning - Privacy and Incentive, 2020

A Unified q-Memorization Framework for Asynchronous Stochastic Optimization.

Bin Gu, Wenhan Xian, Zhouyuan Huo, Cheng Deng, Heng Huang

J. Mach. Learn. Res., 2020

Improved Bilevel Model: Fast and Optimal Algorithm with Theoretical Guarantee.

Junyi Li, Bin Gu, Heng Huang

CoRR, 2020

Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning.

Bin Gu, An Xu, Zhouyuan Huo, Cheng Deng, Heng Huang

CoRR, 2020

Faster On-Device Training Using New Federated Momentum Algorithm.

Zhouyuan Huo, Qian Yang, Bin Gu, Lawrence Carin, Heng Huang

CoRR, 2020

Large Batch Training Does Not Need Warmup.

Zhouyuan Huo, Bin Gu, Heng Huang

CoRR, 2020

Semi-Supervised Multi-Label Learning from Crowds via Deep Sequential Generative Model.

Wanli Shi, Victor S. Sheng, Xiang Li, Bin Gu

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data.

Bin Gu, Zhiyuan Dang, Xiang Li, Heng Huang

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Fast OSCAR and OWL Regression via Safe Screening Rules.

Runxue Bao, Bin Gu, Heng Huang

Proceedings of the 37th International Conference on Machine Learning, 2020

Safe Sample Screening for Robust Support Vector Machine.

Zhou Zhai, Bin Gu, Xiang Li, Heng Huang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization.

Wanli Shi, Bin Gu, Xiang Li, Heng Huang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Majority Voting and Pairing with Multiple Noisy Labeling.

Victor S. Sheng, Jing Zhang, Bin Gu, Xindong Wu

IEEE Trans. Knowl. Data Eng., 2019

Efficient inexact proximal gradient algorithms for structured sparsity-inducing norm.

Bin Gu, Xiang Geng, Xiang Li, Guansheng Zheng

Neural Networks, 2019

Tackle Balancing Constraint for Incremental Semi-Supervised Support Vector Learning.

Shuyang Yu, Bin Gu, Kunpeng Ning, Haiyan Chen, Jian Pei, Heng Huang

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization.

Wanli Shi, Bin Gu, Xiang Li, Xiang Geng, Heng Huang

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Asynchronous Stochastic Frank-Wolfe Algorithms for Non-Convex Optimization.

Bin Gu, Wenhan Xian, Heng Huang

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Scalable Semi-Supervised SVM via Triply Stochastic Gradients.

Xiang Geng, Bin Gu, Xiang Li, Wanli Shi, Guansheng Zheng, Heng Huang

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Efficient Approximate Solution Path Algorithm for Order Weight L_1-Norm with Accuracy Guarantee.

Runxue Bao, Bin Gu, Heng Huang

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization.

Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Scalable and Efficient Pairwise Learning to Achieve Statistical Accuracy.

Bin Gu, Zhouyuan Huo, Heng Huang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

A Solution Path Algorithm for General Parametric Quadratic Programming Problem.

Bin Gu, Victor S. Sheng

IEEE Trans. Neural Networks Learn. Syst., 2018

Chunk incremental learning for cost-sensitive hinge loss support vector machine.

Bin Gu, Xin Quan, Yunhua Gu, Victor S. Sheng, Guansheng Zheng

Pattern Recognit., 2018

A regularization path algorithm for support vector ordinal regression.

Bin Gu

Neural Networks, 2018

Sparse regression with output correlation for cardiac ejection fraction estimation.

Bin Gu, Yingying Shan, Victor S. Sheng, Yuhui Zheng, Shuo Li

Inf. Sci., 2018

The convergence of linear classifiers on large sparse data.

Xiang Li, Huaimin Wang, Bin Gu, Charles X. Ling

Neurocomputing, 2018

Training Neural Networks Using Features Replay.

Zhouyuan Huo, Bin Gu, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

New Incremental Learning Algorithm for Semi-Supervised Support Vector Machine.

Bin Gu, Xiao-Tong Yuan, Songcan Chen, Heng Huang

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Accelerated Asynchronous Greedy Coordinate Descent Algorithm for SVMs.

Bin Gu, Yingying Shan, Xiang Geng, Guansheng Zheng

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Faster Training Algorithms for Structured Sparsity-Inducing Norm.

Bin Gu, Xingwang Ju, Xiang Li, Guansheng Zheng

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Decoupled Parallel Backpropagation with Convergence Guarantee.

Zhouyuan Huo, Bin Gu, Qian Yang, Heng Huang

Proceedings of the 35th International Conference on Machine Learning, 2018

Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines.

Bin Gu, Zhouyuan Huo, Cheng Deng, Heng Huang

Proceedings of the 35th International Conference on Machine Learning, 2018

Asynchronous Doubly Stochastic Group Regularized Learning.

Bin Gu, Zhouyuan Huo, Heng Huang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Accelerated Method for Stochastic Composition Optimization With Nonsmooth Regularization.

Zhouyuan Huo, Bin Gu, Ji Liu, Heng Huang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Asynchronous Doubly Stochastic Sparse Kernel Learning.

Bin Gu, Miao Xin, Zhouyuan Huo, Heng Huang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Inexact Proximal Gradient Methods for Non-Convex and Non-Smooth Optimization.

Bin Gu, De Wang, Zhouyuan Huo, Heng Huang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Structural Minimax Probability Machine.

Bin Gu, Xingming Sun, Victor S. Sheng

IEEE Trans. Neural Networks Learn. Syst., 2017

A Robust Regularization Path Algorithm for ν-Support Vector Classification.

Bin Gu, Victor S. Sheng

IEEE Trans. Neural Networks Learn. Syst., 2017

Cross Validation Through Two-Dimensional Solution Surface for Cost-Sensitive SVM.

Bin Gu, Victor S. Sheng, KengYeow Tay, Walter Romano, Shuo Li

IEEE Trans. Pattern Anal. Mach. Intell., 2017

Accelerated Method for Stochastic Composition Optimization with Nonsmooth Regularization.

Zhouyuan Huo, Bin Gu, Heng Huang

CoRR, 2017

Triply Stochastic Gradients on Multiple Kernel Learning.

Xiang Li, Bin Gu, Shuang Ao, Huaimin Wang, Charles X. Ling

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Groups-Keeping Solution Path Algorithm for Sparse Regression with Automatic Feature Grouping.

Bin Gu, Guodong Liu, Heng Huang

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

2016

Decoupled Asynchronous Proximal Stochastic Gradient Descent with Variance Reduction.

Zhouyuan Huo, Bin Gu, Heng Huang

CoRR, 2016

Inexact Proximal Gradient Methods for Non-convex and Non-smooth Optimization.

Bin Gu, Zhouyuan Huo, Heng Huang

CoRR, 2016

Zeroth-order Asynchronous Doubly Stochastic Algorithm with Variance Reduction.

Bin Gu, Zhouyuan Huo, Heng Huang

CoRR, 2016

Asynchronous Doubly Stochastic Proximal Optimization with Variance Reduction.

Bin Gu, Zhouyuan Huo, Heng Huang

CoRR, 2016

2015

Incremental Support Vector Learning for Ordinal Regression.

Bin Gu, Victor S. Sheng, KengYeow Tay, Walter Romano, Shuo Li

IEEE Trans. Neural Networks Learn. Syst., 2015

Incremental learning for ν-Support Vector Regression.

Bin Gu, Victor S. Sheng, Zhijie Wang, Derek Ho, Said Osman, Shuo Li

Neural Networks, 2015

Data Sparseness in Linear SVM.

Xiang Li, Huaimin Wang, Bin Gu, Charles X. Ling

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Bi-Parameter Space Partition for Cost-Sensitive SVM.

Bin Gu, Victor S. Sheng, Shuo Li

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

A New Generalized Error Path Algorithm for Model Selection.

Bin Gu, Charles X. Ling

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Direct Estimation of Cardiac Biventricular Volumes With an Adapted Bayesian Formulation.

Zhijie Wang, Mohamed Ben Salah, Bin Gu, Ali Islam, Aashish Goela, Shuo Li

IEEE Trans. Biomed. Eng., 2014

Cost-sensitive learning for defect escalation.

Victor S. Sheng, Bin Gu, Wei Fang, Jian Wu

Knowl. Based Syst., 2014

2013

Feasibility and Finite Convergence Analysis for Accurate On-Line $\nu$-Support Vector Machine.

Bin Gu, Victor S. Sheng

IEEE Trans. Neural Networks Learn. Syst., 2013

2012

Regularization Path for ν-Support Vector Classification.

Bin Gu, Jiandong Wang, Guansheng Zheng, Yuecheng Yu

IEEE Trans. Neural Networks Learn. Syst., 2012

Accurate on-line v-support vector learning.

Bin Gu, Jiandong Wang, Yuecheng Yu, Guansheng Zheng, Yufan Huang, Tao Xu

Neural Networks, 2012

2010

Semi-supervised Distributed Clustering with Mahalanobis Distance Metric Learning.

Yuecheng Yu, Jiandong Wang, Guansheng Zheng, Bin Gu

J. Digit. Content Technol. its Appl., 2010

Ordinal-Class Core Vector Machine.

Bin Gu, Jiandong Wang, Tao Li

J. Comput. Sci. Technol., 2010

2008

On-line off-line Ranking Support Vector Machine and analysis.

Bin Gu, Jiandong Wang, Haiyan Chen

Proceedings of the International Joint Conference on Neural Networks, 2008