Bin Gu

ORCID

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 154

Top Venues

CoRR

AAAI

IEEE Trans. Neural Networks Learn. Syst.

KDD

Publications

Nan Yin, Mengzhu Wang, Zhenghan Chen, Li Shen, Huan Xiong, Bin Gu, Xiao Luo
DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption. ICLR (2024)
Haozhen Zhang, Hualin Zhang, Bin Gu, Yi Chang
Subspace Selection based Prompt Tuning with Nonconvex Nonsmooth Black-Box Optimization. KDD (2024)
Nan Yin, Mengzhu Wang, Li Shen, Hitesh Laxmichand Patel, Baopu Li, Bin Gu, Huan Xiong
Continuous Spiking Graph Neural Networks. CoRR (2024)
Velibor Bojkovic, Srinivas Anumasa, Giulia De Masi, Bin Gu, Huan Xiong
Data Driven Threshold and Potential Initialization for Spiking Neural Networks. AISTATS (2024)
Nan Yin, Mengzhu Wang, Zhenghan Chen, Giulia De Masi, Bin Gu, Huan Xiong
Dynamic Spiking Graph Neural Networks. CoRR (2024)
Mengnan Qi, Yufan Huang, Yongqiang Yao, Maoquan Wang, Bin Gu, Neel Sundaresan
Is Next Token Prediction Sufficient for GPT? Exploration on Code Logic Comprehension. CoRR (2024)
Xinzhe Yuan, William de Vazelhes, Bin Gu, Huan Xiong
New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions. ICLR (2024)
William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu
Iterative Regularization with k-Support Norm: an Important Complement to Sparse Recovery. CoRR (2024)
William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu
Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery. AAAI (2024)
Bin Gu, Xiyuan Wei, Hualin Zhang, Yi Chang, Heng Huang
Obtaining Lower Query Complexities Through Lightweight Zeroth-Order Proximal Gradient Algorithms. Neural Comput. 36 (5) (2024)
Longkang Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
Federated Causal Discovery from Heterogeneous Data. ICLR (2024)
Xiaofeng Wu, Velibor Bojkovic, Bin Gu, Kun Suo, Kai Zou
FTBC: Forward Temporal Bias Correction for Optimizing ANN-SNN Conversion. CoRR (2024)
Zhuang Qian, Shufei Zhang, Kaizhu Huang, Qiufeng Wang, Xinping Yi, Bin Gu, Huan Xiong
Perturbation diversity certificates robust generalization. Neural Networks 172 (2024)
Chengqian Gao, William de Vazelhes, Hualin Zhang, Bin Gu, Zhiqiang Xu
Hard-Thresholding Meets Evolution Strategies in Reinforcement Learning. CoRR (2024)
Wanli Shi, Yi Chang, Bin Gu
Double Momentum Method for Lower-Level Constrained Bilevel Optimization. CoRR (2024)
Zhiyuan Dang, Bin Gu, Cheng Deng, Heng Huang
Asynchronous Parallel Large-Scale Gaussian Process Regression. IEEE Trans. Neural Networks Learn. Syst. 35 (6) (2024)
Hilal AlQuabeh, William de Vazelhes, Bin Gu
Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging. AAAI (2024)
Ganyu Wang, Qingsong Zhang, Xiang Li, Boyu Wang, Bin Gu, Charles X. Ling
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization. Mach. Learn. 113 (9) (2024)
Xinyue Liu, Hualin Zhang, Bin Gu, Hong Chen
General Stability Analysis for Zeroth-Order Optimization Algorithms. ICLR (2024)
Zhou Zhai, Wanli Shi, Heng Huang, Yi Chang, Bin Gu
Learning Sampling Policy to Achieve Fewer Queries for Zeroth-Order Optimization. AISTATS (2024)
Bhaskar Mukhoty, Hilal AlQuabeh, Giulia De Masi, Huan Xiong, Bin Gu
Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks. ICLR (2024)
Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
Federated Causal Discovery from Heterogeneous Data. CoRR (2024)
Hong Chen, Xuelin Zhang, Tieliang Gong, Bin Gu, Feng Zheng
Error Density-dependent Empirical Risk Minimization. Expert Syst. Appl. 254 (2024)
Yajing Fan, Wanli Shi, Yi Chang, Bin Gu
Fast and Adversarial Robust Kernelized SDU Learning. AISTATS (2024)
Haiyan Jiang, Vincent Zoonekynd, Giulia De Masi, Bin Gu, Huan Xiong
TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks. ICLR (2024)
Chenkang Zhang, Heng Huang, Bin Gu
Tackle balancing constraints in semi-supervised ordinal regression. Mach. Learn. 113 (5) (2024)
Diyang Li, Charles Ling, Zhiqiang Xu, Huan Xiong, Bin Gu
Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s). ICLR (2024)
Srinivas Anumasa, Bhaskar Mukhoty, Velibor Bojkovic, Giulia De Masi, Huan Xiong, Bin Gu
Enhancing Training of Spiking Neural Network with Stochastic Latency. AAAI (2024)
Zhou Zhai, Heng Huang, Bin Gu
Kernel Path for Semisupervised Support Vector Machine. IEEE Trans. Neural Networks Learn. Syst. 35 (2) (2024)
Nan Yin, Mengzhu Wang, Zhenghan Chen, Giulia De Masi, Huan Xiong, Bin Gu
Dynamic Spiking Graph Neural Networks. AAAI (2024)
Nan Yin, Li Shen, Huan Xiong, Bin Gu, Chong Chen, Xian-Sheng Hua, Siwei Liu, Xiao Luo
Messages are Never Propagated Alone: Collaborative Hypergraph Neural Network for Time-Series Forecasting. IEEE Trans. Pattern Anal. Mach. Intell. 46 (4) (2024)
Hilal AlQuabeh, William de Vazelhes, Bin Gu
Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging. CoRR (2024)
Huan Xiong, Lei Huang, Wenston J. T. Zang, Xiantong Zhen, Guo-Sen Xie, Bin Gu, Le Song
On the Number of Linear Regions of Convolutional Neural Networks With Piecewise Linear Activations. IEEE Trans. Pattern Anal. Mach. Intell. 46 (7) (2024)
Haiyan Chen, Ying Yu, Yizhen Jia, Bin Gu
Incremental learning for transductive support vector machine. Pattern Recognit. 133 (2023)
Hilal AlQuabeh, Bhaskar Mukhoty, Bin Gu
Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory. ACML (2023)
Diyang Li, Bin Gu
When Online Learning Meets ODE: Learning without Forgetting on Variable Feature Space. AAAI (2023)
Zhou Zhai, Lei Luo, Heng Huang, Bin Gu
Faster Fair Machine via Transferring Fairness Constraints to Virtual Samples. AAAI (2023)
Jun Chen, Hong Chen, Xue Jiang, Bin Gu, Weifu Li, Tieliang Gong, Feng Zheng
On the Stability and Generalization of Triplet Learning. AAAI (2023)
Bin Gu, Chenkang Zhang, Zhouyuan Huo, Heng Huang
A new large-scale learning algorithm for generalized additive models. Mach. Learn. 112 (9) (2023)
Bin Gu, Ziran Xiong, Xiang Li, Zhou Zhai, Guansheng Zheng
Kernel Path for ν-Support Vector Classification. IEEE Trans. Neural Networks Learn. Syst. 34 (1) (2023)
Jun Chen, Hong Chen, Bin Gu, Hao Deng
Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization. NeurIPS (2023)
Chenkang Zhang, Lei Luo, Bin Gu
Denoising Multi-Similarity Formulation: A Self-Paced Curriculum-Driven Approach for Robust Metric Learning. AAAI (2023)
Xiaohan Zhao, Hualin Zhang, Zhouyuan Huo, Bin Gu
Accelerated On-Device Forward Neural Network Training with Module-Wise Descending Asynchronism. NeurIPS (2023)
Haiyan Jiang, Srinivas Anumasa, Giulia De Masi, Huan Xiong, Bin Gu
A Unified Optimization Framework of ANN-SNN Conversion: Towards Optimal Mapping from Activation Values to Firing Rates. ICML (2023)
Bhaskar Mukhoty, Velibor Bojkovic, William de Vazelhes, Xiaohan Zhao, Giulia De Masi, Huan Xiong, Bin Gu
Direct Training of SNN using Local Zeroth Order Method. NeurIPS (2023)
Ganyu Wang, Qingsong Zhang, Li Xiang, Boyu Wang, Bin Gu, Charles Ling
Secure and Fast Asynchronous Vertical Federated Learning via Cascaded Hybrid Optimization. CoRR (2023)
Hongchang Gao, Bin Gu, My T. Thai
On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network. AISTATS (2023)
Ganyu Wang, Bin Gu, Qingsong Zhang, Xiang Li, Boyu Wang, Charles X. Ling
A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning. NeurIPS (2023)
Hualin Zhang, Bin Gu
Faster Gradient-Free Methods for Escaping Saddle Points. ICLR (2023)
Bhaskar Mukhoty, Velibor Bojkovic, William de Vazelhes, Giulia De Masi, Huan Xiong, Bin Gu
Energy Efficient Training of SNN using Local Zeroth Order Method. CoRR (2023)
Chenkang Zhang, Wanli Shi, Lei Luo, Bin Gu
Doubly Robust AUC Optimization against Noisy and Adversarial Samples. KDD (2023)
Jiahuan Wang, Jun Chen, Hong Chen, Bin Gu, Weifu Li, Xin Tang
Stability-Based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning. AAAI (2023)
Huimin Wu, Wanli Shi, Chenkang Zhang, Bin Gu
Self-Adaptive Perturbation Radii for Adversarial Training. KDD (2023)
Ziran Xiong, Charles X. Ling, Bin Gu
Kernel Error Path Algorithm. IEEE Trans. Neural Networks Learn. Syst. 34 (11) (2023)
Hilal AlQuabeh, Bhaskar Mukhoty, Bin Gu
Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory. CoRR (2023)
Qingsong Zhang, Bin Gu, Zhiyuan Dang, Cheng Deng, Heng Huang
Desirable Companion for Vertical Federated Learning: New Zeroth-Order Gradient Based Algorithm. CoRR (2022)
Yuzhen Han, Ruben Solozabal, Jing Dong, Xingyu Zhou, Martin Takác, Bin Gu
Learning to Control under Time-Varying Environment. CoRR (2022)
Bin Gu, An Xu, Zhouyuan Huo, Cheng Deng, Heng Huang
Privacy-Preserving Asynchronous Vertical Federated Learning Algorithms for Multiparty Collaborative Learning. IEEE Trans. Neural Networks Learn. Syst. 33 (11) (2022)
Haiyan Chen, Yizhen Jia, Jiaming Ge, Bin Gu
Incremental learning algorithm for large-scale semi-supervised ordinal regression. Neural Networks 149 (2022)
Hualin Zhang, Huan Xiong, Bin Gu
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients. NeurIPS (2022)
Junyi Li, Bin Gu, Heng Huang
A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse. AAAI (2022)
Bin Gu, Chenkang Zhang, Huan Xiong, Heng Huang
Balanced Self-Paced Learning for AUC Maximization. AAAI (2022)
Runxue Bao, Bin Gu, Heng Huang
An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification. CIKM (2022)
Ziran Xiong, Wanli Shi, Bin Gu
End-to-End Semi-Supervised Ordinal Regression AUC Maximization with Convolutional Kernel Networks. KDD (2022)
Zhiyuan Dang, Xiang Li, Bin Gu, Cheng Deng, Heng Huang
Large-Scale Nonlinear AUC Maximization via Triply Stochastic Gradients. IEEE Trans. Pattern Anal. Mach. Intell. 44 (3) (2022)
Xingyu Qu, Diyang Li, Xiaohan Zhao, Bin Gu
GAGA: Deciphering Age-path of Generalized Self-paced Regularizer. NeurIPS (2022)
Bin Gu, Chenkang Zhang, Huan Xiong, Heng Huang
Balanced Self-Paced Learning for AUC Maximization. CoRR (2022)
Bin Gu, Zhiyuan Dang, Zhouyuan Huo, Cheng Deng, Heng Huang
Scaling Up Generalized Kernel Methods. IEEE Trans. Pattern Anal. Mach. Intell. 44 (7) (2022)
Bin Gu, Zhou Zhai, Xiang Li, Heng Huang
Towards Fairer Classifier via True Fairness Score Path. CIKM (2022)
Diyang Li, Bin Gu
Chunk Dynamic Updating for Group Lasso with ODEs. AAAI (2022)
Hongchang Gao, Bin Gu, My T. Thai
Stochastic Bilevel Distributed Optimization over a Network. CoRR (2022)
Alexander V. Gasnikov, Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takác, Pavel E. Dvurechensky, Bin Gu
The power of first-order smooth optimization for black-box non-smooth problems. ICML (2022)
Zhengqing Gao, Huimin Wu, Martin Takác, Bin Gu
Towards Practical Large Scale Non-Linear Semi-Supervised Learning with Balancing Constraints. CIKM (2022)
Xingyu Qu, Diyang Li, Xiaohan Zhao, Bin Gu
GAGA: Deciphering Age-path of Generalized Self-paced Regularizer. CoRR (2022)
Hualin Zhang, Huan Xiong, Bin Gu
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients. CoRR (2022)
Huimin Wu, William de Vazelhes, Bin Gu
Efficient Semi-Supervised Adversarial Training without Guessing Labels. ICDM (2022)
William de Vazelhes, Hualin Zhang, Huimin Wu, Xiao-Tong Yuan, Bin Gu
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity. CoRR (2022)
Wanli Shi, Hongchang Gao, Bin Gu
Gradient-Free Method for Heavily Constrained Nonconvex Optimization. ICML (2022)
William de Vazelhes, Hualin Zhang, Huimin Wu, Xiaotong Yuan, Bin Gu
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity. NeurIPS (2022)
Runxue Bao, Bin Gu, Heng Huang
An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification. CoRR (2022)
Wanli Shi, Bin Gu, Xiang Li, Cheng Deng, Heng Huang
Triply stochastic gradient method for large-scale nonlinear similar unlabeled classification. Mach. Learn. 110 (8) (2021)
Bin Gu, Yingying Shan, Xin Quan, Guansheng Zheng
Accelerating Sequential Minimal Optimization via Stochastic Subgradient Descent. IEEE Trans. Cybern. 51 (4) (2021)
Wanli Shi, Bin Gu
Improved Penalty Method via Doubly Stochastic Gradients for Bilevel Hyperparameter Optimization. AAAI (2021)
Zhou Zhai, Bin Gu, Heng Huang
Learning Sampling Policy for Faster Derivative Free Optimization. CoRR (2021)
Bin Gu, Zhou Zhai, Xiang Li, Heng Huang
Finding Age Path of Self-Paced Learning. ICDM (2021)
Bin Gu, Xiyuan Wei, Shangqian Gao, Ziran Xiong, Cheng Deng, Heng Huang
Black-Box Reductions for Zeroth-Order Gradient Algorithms to Achieve Lower Query Complexity. J. Mach. Learn. Res. 22 (2021)
Huimin Wu, Zhengmian Hu, Bin Gu
Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients. CoRR (2021)
Qingsong Zhang, Bin Gu, Cheng Deng, Songxiang Gu, Liefeng Bo, Jian Pei, Heng Huang
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization. KDD (2021)
Qingsong Zhang, Bin Gu, Cheng Deng, Songxiang Gu, Liefeng Bo, Jian Pei, Heng Huang
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization. CoRR (2021)
Bin Gu, Ziran Xiong, Shuyang Yu, Guansheng Zheng
A kernel path algorithm for general parametric quadratic programming problem. Pattern Recognit. 116 (2021)
Zhouyuan Huo, Bin Gu, Heng Huang
Large Batch Optimization for Deep Learning Using New Complete Layer-Wise Adaptive Rate Scaling. AAAI (2021)
Bin Gu, Xiang Geng, Xiang Li, Wanli Shi, Guansheng Zheng, Cheng Deng, Heng Huang
Scalable Kernel Ordinal Regression via Doubly Stochastic Gradients. IEEE Trans. Neural Networks Learn. Syst. 32 (8) (2021)
Huimin Wu, Zhengmian Hu, Bin Gu
Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients. AAAI (2021)
Junyi Li, Bin Gu, Heng Huang
A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse. CoRR (2021)
Bin Gu, Charles X. Ling
Generalized error path algorithm. Pattern Recognit. 120 (2021)
Qingsong Zhang, Bin Gu, Cheng Deng, Heng Huang
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating. AAAI (2021)
Qingsong Zhang, Bin Gu, Cheng Deng, Heng Huang
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating. CoRR (2021)
Bin Gu, Guodong Liu, Yanfu Zhang, Xiang Geng, Heng Huang
Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm. CoRR (2021)
Bin Gu, Xiang Geng, Wanli Shi, Yingying Shan, Yufang Huang, Zhijie Wang, Guansheng Zheng
Solving large-scale support vector ordinal regression with asynchronous parallel coordinate descent algorithms. Pattern Recognit. 109 (2021)
Qingsong Zhang, Bin Gu, Zhiyuan Dang, Cheng Deng, Heng Huang
Desirable Companion for Vertical Federated Learning: New Zeroth-Order Gradient Based Algorithm. CIKM (2021)

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Publication Activity (10 Years)

Top Topics

Top Venues

Bin Gu