Gu, Bin

85 publications

NeurIPS 2025 Accelerated Vertical Federated Adversarial Learning Through Decoupling Layer-Wise Dependencies Tianxing Man, Yu Bai, Ganyu Wang, Jinjie Fang, Haoran Fang, Bin Gu, Yi Chang

ICLR 2025 Collaborative Discrete-Continuous Black-Box Prompt Learning for Language Models Hualin Zhang, Haozhen Zhang, Zhekai Liu, Bin Gu, Yi Chang

AAAI 2025 Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent Jun Chen, Hong Chen, Bin Gu, Guodong Liu, Yingjie Wang, Weifu Li

ICLR 2025 Event-Driven Online Vertical Federated Learning Ganyu Wang, Boyu Wang, Bin Gu, Charles Ling

ICML 2025 FedOne: Query-Efficient Federated Learning for Black-Box Discrete Prompt Learning Ganyu Wang, Jinjie Fang, Maxwell Juncheng Yin, Bin Gu, Xi Chen, Boyu Wang, Yi Chang, Charles Ling

ICLR 2025 Improving Generalization and Robustness in SNNs Through Signed Rate Encoding and Sparse Encoding Attacks Bhaskar Mukhoty, Hilal AlQuabeh, Bin Gu

AAAI 2025 Leveraging First and Zeroth-Order Gradient to Address Imbalanced Black-Box Prompt Tuning via Minimax Optimization Haozhen Zhang, Zhaogeng Liu, Bin Gu, Yi Chang

ICML 2025 Optimization over Sparse Support-Preserving Sets: Two-Step Projection with Global Optimality Guarantees William De Vazelhes, Xiaotong Yuan, Bin Gu

CVPR 2025 Query Efficient Black-Box Visual Prompting with Subspace Learning Zhaogeng Liu, Haozhen Zhang, Hualin Zhang, Xingchen Li, Wanli Shi, Bin Gu, Yi Chang

ICML 2025 Temporal Misalignment in ANN-SNN Conversion and Its Mitigation via Probabilistic Spiking Neurons Velibor Bojkovic, Xiaofeng Wu, Bin Gu

ICLR 2024 Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks Bhaskar Mukhoty, Hilal AlQuabeh, Giulia De Masi, Huan Xiong, Bin Gu

ICLR 2024 DREAM: Dual Structured Exploration with Mixup for Open-Set Graph Domain Adaption Nan Yin, Mengzhu Wang, Zhenghan Chen, Li Shen, Huan Xiong, Bin Gu, Xiao Luo

AISTATS 2024 Data Driven Threshold and Potential Initialization for Spiking Neural Networks Velibor Bojkovic, Srinivas Anumasa, Giulia De Masi, Bin Gu, Huan Xiong

ICML 2024 Double Momentum Method for Lower-Level Constrained Bilevel Optimization Wanli Shi, Yi Chang, Bin Gu

AAAI 2024 Dynamic Spiking Graph Neural Networks Nan Yin, Mengzhu Wang, Zhenghan Chen, Giulia De Masi, Huan Xiong, Bin Gu

AAAI 2024 Enhancing Training of Spiking Neural Network with Stochastic Latency Srinivas Anumasa, Bhaskar Mukhoty, Velibor Bojkovic, Giulia De Masi, Huan Xiong, Bin Gu

ECCV 2024 Exploring Vulnerabilities in Spiking Neural Networks: Direct Adversarial Attacks on Raw Event Data Yanmeng Yao, Xiaohan Zhao, Bin Gu

ECCV 2024 FTBC: Forward Temporal Bias Correction for Optimizing ANN-SNN Conversion Xiaofeng Wu, Velibor Bojkovic, Bin Gu, Kun Suo, Kai Zou

AISTATS 2024 Fast and Adversarial Robust Kernelized SDU Learning Yajing Fan, Wanli Shi, Yi Chang, Bin Gu

ICLR 2024 Federated Causal Discovery from Heterogeneous Data Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang

IJCAI 2024 Fine-Grained Analysis of Stability and Generalization for Stochastic Bilevel Optimization Xuelin Zhang, Hong Chen, Bin Gu, Tieliang Gong, Feng Zheng

ICLR 2024 General Stability Analysis for Zeroth-Order Optimization Algorithms Xinyue Liu, Hualin Zhang, Bin Gu, Hong Chen

IJCAI 2024 Hard-Thresholding Meets Evolution Strategies in Reinforcement Learning Chengqian Gao, William de Vazelhes, Hualin Zhang, Bin Gu, Zhiqiang Xu

NeurIPS 2024 How Does Black-Box Impact the Learning Guarantee of Stochastic Compositional Optimization? Jun Chen, Hong Chen, Bin Gu

AAAI 2024 Iterative Regularization with K-Support Norm: An Important Complement to Sparse Recovery William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu

ICLR 2024 Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s) Diyang Li, Charles Ling, Zhiqiang Xu, Huan Xiong, Bin Gu

AISTATS 2024 Learning Sampling Policy to Achieve Fewer Queries for Zeroth-Order Optimization Zhou Zhai, Wanli Shi, Heng Huang, Yi Chang, Bin Gu

AAAI 2024 Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging Hilal AlQuabeh, William de Vazelhes, Bin Gu

ICML 2024 NDOT: Neuronal Dynamics-Based Online Training for Spiking Neural Networks Haiyan Jiang, Giulia De Masi, Huan Xiong, Bin Gu

ICLR 2024 New Insight of Variance Reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions Xinzhe Yuan, William de Vazelhes, Bin Gu, Huan Xiong

JMLR 2024 On the Intrinsic Structures of Spiking Neural Networks Shao-Qun Zhang, Jia-Yi Chen, Jin-Hui Wu, Gao Zhang, Huan Xiong, Bin Gu, Zhi-Hua Zhou

MLJ 2024 Secure and Fast Asynchronous Vertical Federated Learning via Cascaded Hybrid Optimization Ganyu Wang, Qingsong Zhang, Xiang Li, Boyu Wang, Bin Gu, Charles X. Ling

ICLR 2024 TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks Haiyan Jiang, Vincent Zoonekynd, Giulia De Masi, Bin Gu, Huan Xiong

MLJ 2024 Tackle Balancing Constraints in Semi-Supervised Ordinal Regression Chenkang Zhang, Heng Huang, Bin Gu

MLJ 2023 A New Large-Scale Learning Algorithm for Generalized Additive Models Bin Gu, Chenkang Zhang, Zhouyuan Huo, Heng Huang

ICML 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

NeurIPS 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

NeurIPS 2023 Accelerated On-Device Forward Neural Network Training with Module-Wise Descending Asynchronism Xiaohan Zhao, Hualin Zhang, Zhouyuan Huo, Bin Gu

AAAI 2023 Denoising Multi-Similarity Formulation: A Self-Paced Curriculum-Driven Approach for Robust Metric Learning Chenkang Zhang, Lei Luo, Bin Gu

NeurIPS 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

AAAI 2023 Faster Fair Machine via Transferring Fairness Constraints to Virtual Samples Zhou Zhai, Lei Luo, Heng Huang, Bin Gu

ICLR 2023 Faster Gradient-Free Methods for Escaping Saddle Points Hualin Zhang, Bin Gu

NeurIPS 2023 Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization Jun Chen, Hong Chen, Bin Gu, Hao Deng

AISTATS 2023 On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network Hongchang Gao, Bin Gu, My T. Thai

AAAI 2023 On the Stability and Generalization of Triplet Learning Jun Chen, Hong Chen, Xue Jiang, Bin Gu, Weifu Li, Tieliang Gong, Feng Zheng

AAAI 2023 Stability-Based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning Jiahuan Wang, Jun Chen, Hong Chen, Bin Gu, Weifu Li, Xin Tang

ACML 2023 Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory Hilal AlQuabeh, Bhaskar Mukhoty, Bin Gu

AAAI 2023 When Online Learning Meets ODE: Learning Without Forgetting on Variable Feature Space Diyang Li, Bin Gu

AAAI 2022 A Fully Single Loop Algorithm for Bilevel Optimization Without Hessian Inverse Junyi Li, Bin Gu, Heng Huang

NeurIPSW 2022 An Accuracy Guaranteed Online Solver for Learning in Dynamic Feature Space Diyang Li, Bin Gu

AAAI 2022 Balanced Self-Paced Learning for AUC Maximization Bin Gu, Chenkang Zhang, Huan Xiong, Heng Huang

AAAI 2022 Chunk Dynamic Updating for Group Lasso with ODEs Diyang Li, Bin Gu

NeurIPS 2022 GAGA: Deciphering Age-Path of Generalized Self-Paced Regularizer Xingyu Qu, Diyang Li, Xiaohan Zhao, Bin Gu

ICML 2022 Gradient-Free Method for Heavily Constrained Nonconvex Optimization Wanli Shi, Hongchang Gao, Bin Gu

ICML 2022 The Power of First-Order Smooth Optimization for Black-Box Non-Smooth Problems Alexander Gasnikov, Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takac, Pavel Dvurechensky, Bin Gu

NeurIPS 2022 Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity William de Vazelhes, Hualin Zhang, Huimin Wu, Xiaotong Yuan, Bin Gu

NeurIPS 2022 Zeroth-Order Negative Curvature Finding: Escaping Saddle Points Without Gradients Hualin Zhang, Huan Xiong, Bin Gu

JMLR 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

AAAI 2021 Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients Huimin Wu, Zhengmian Hu, Bin Gu

AAAI 2021 Improved Penalty Method via Doubly Stochastic Gradients for Bilevel Hyperparameter Optimization Wanli Shi, Bin Gu

AAAI 2021 Large Batch Optimization for Deep Learning Using New Complete Layer-Wise Adaptive Rate Scaling Zhouyuan Huo, Bin Gu, Heng Huang

AAAI 2021 Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating Qingsong Zhang, Bin Gu, Cheng Deng, Heng Huang

MLJ 2021 Triply Stochastic Gradient Method for Large-Scale Nonlinear Similar Unlabeled Classification Wanli Shi, Bin Gu, Xiang Li, Cheng Deng, Heng Huang

JMLR 2020 A Unified Q-Memorization Framework for Asynchronous Stochastic Optimization Bin Gu, Wenhan Xian, Zhouyuan Huo, Cheng Deng, Heng Huang

ICML 2020 Fast OSCAR and OWL Regression via Safe Screening Rules Runxue Bao, Bin Gu, Heng Huang

AAAI 2020 Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization Wanli Shi, Bin Gu, Xiang Li, Heng Huang

AAAI 2020 Safe Sample Screening for Robust Support Vector Machine Zhou Zhai, Bin Gu, Xiang Li, Heng Huang

IJCAI 2019 Asynchronous Stochastic Frank-Wolfe Algorithms for Non-Convex Optimization Bin Gu, Wenhan Xian, Heng Huang

AAAI 2019 Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang

IJCAI 2019 Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization Wanli Shi, Bin Gu, Xiang Li, Xiang Geng, Heng Huang

IJCAI 2019 Scalable Semi-Supervised SVM via Triply Stochastic Gradients Xiang Geng, Bin Gu, Xiang Li, Wanli Shi, Guansheng Zheng, Heng Huang

AAAI 2019 Scalable and Efficient Pairwise Learning to Achieve Statistical Accuracy Bin Gu, Zhouyuan Huo, Heng Huang

IJCAI 2018 Accelerated Asynchronous Greedy Coordinate Descent Algorithm for SVMs Bin Gu, Yingying Shan, Xiang Geng, Guansheng Zheng

AAAI 2018 Accelerated Method for Stochastic Composition Optimization with Nonsmooth Regularization Zhouyuan Huo, Bin Gu, Ji Liu, Heng Huang

AISTATS 2018 Asynchronous Doubly Stochastic Group Regularized Learning Bin Gu, Zhouyuan Huo, Heng Huang

AAAI 2018 Asynchronous Doubly Stochastic Sparse Kernel Learning Bin Gu, Miao Xin, Zhouyuan Huo, Heng Huang

ICML 2018 Decoupled Parallel Backpropagation with Convergence Guarantee Zhouyuan Huo, Bin Gu, Yang, Heng Huang

ICML 2018 Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines Bin Gu, Zhouyuan Huo, Cheng Deng, Heng Huang

IJCAI 2018 Faster Training Algorithms for Structured Sparsity-Inducing Norm Bin Gu, Xingwang Ju, Xiang Li, Guansheng Zheng

AAAI 2018 Inexact Proximal Gradient Methods for Non-Convex and Non-Smooth Optimization Bin Gu, De Wang, Zhouyuan Huo, Heng Huang

NeurIPS 2018 Training Neural Networks Using Features Replay Zhouyuan Huo, Bin Gu, Heng Huang

UAI 2017 Triply Stochastic Gradients on Multiple Kernel Learning Xiang Li, Bin Gu, Shuang Ao, Huaimin Wang, Charles X. Ling

ICML 2015 A New Generalized Error Path Algorithm for Model Selection Bin Gu, Charles Ling

IJCAI 2015 Bi-Parameter Space Partition for Cost-Sensitive SVM Bin Gu, Victor S. Sheng, Shuo Li

IJCAI 2015 Data Sparseness in Linear SVM Xiang Li, Huaimin Wang, Bin Gu, Charles X. Ling