Bin Gu

212 papers A* 83A 10B 1C 1Journal 112Unranked 4
YearRankTypeTitle / Venue / Authors
2025 — conf
Arabic Dataset for LLM Safeguard Evaluation.
NAACL (Long Papers)
Yasser Ashraf, Yuxia Wang, Bin Gu, Preslav Nakov, Timothy Baldwin
2025 A* conf
Collaborative Discrete-Continuous Black-Box Prompt Learning for Language Models.
ICLR
Hualin Zhang, Haozhen Zhang, Zhekai Liu, Bin Gu, Yi Chang
2025 — conf
Enhancing Black-Box Adversarial Attacks on Discrete Sequential Data via Bilevel Bayesian Optimization in Hybrid Spaces.
KDD (1)
Tianxing Man, Xingchen Li, Zhaogeng Liu, Haozhen Zhang, Bin Gu, Yi Chang
2025 A* conf
Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent.
AAAI
Jun Chen, Hong Chen, Bin Gu, Guodong Liu, Yingjie Wang, Weifu Li
2025 A* conf
Event-Driven Online Vertical Federated Learning.
ICLR
Ganyu Wang, Boyu Wang, Bin Gu, Charles Ling
2025 J jnl
Event-Driven Online Vertical Federated Learning.
CoRR
Ganyu Wang, Boyu Wang, Bin Gu, Charles Ling
2025 A* conf
FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning.
ICML
Ganyu Wang, Jinjie Fang, Maxwell J. Yin, Bin Gu, Xi Chen, Boyu Wang, Yi Chang, Charles Ling
2025 J jnl
FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning.
CoRR
Ganyu Wang, Jinjie Fang, Maxwell J. Yin, Bin Gu, Xi Chen, Boyu Wang, Charles X. Ling
2025 J jnl
Generalization Bounds of Deep Neural Networks With τ-Mixing Samples.
IEEE Trans. Neural Networks Learn. Syst.
Liyuan Liu, Yaohui Chen, Weifu Li, Yingjie Wang, Bin Gu, Feng Zheng, Hong Chen
2025 J jnl
Global Model Selection for Semi-Supervised Support Vector Machine via Solution Paths.
IEEE Trans. Neural Networks Learn. Syst.
Yajing Fan, Shuyang Yu, Bin Gu, Ziran Xiong, Zhou Zhai, Heng Huang, Yi Chang
2025 J jnl
Global Model Selection via Solution Paths for Robust Support Vector Machine.
IEEE Trans. Pattern Anal. Mach. Intell.
Zhou Zhai, Bin Gu, Cheng Deng, Heng Huang
2025 A* conf
Improving Generalization and Robustness in SNNs Through Signed Rate Encoding and Sparse Encoding Attacks.
ICLR
Bhaskar Mukhoty, Hilal AlQuabeh, Bin Gu
2025 A* conf
Leveraging First and Zeroth-Order Gradient to Address Imbalanced Black-Box Prompt Tuning via Minimax Optimization.
AAAI
Haozhen Zhang, Zhaogeng Liu, Bin Gu, Yi Chang
2025 A* conf
Optimization over Sparse Support-Preserving Sets: Two-Step Projection with Global Optimality Guarantees.
ICML
William de Vazelhes, Xiaotong Yuan, Bin Gu
2025 J jnl
Optimization over Sparse Support-Preserving Sets: Two-Step Projection with Global Optimality Guarantees.
CoRR
William de Vazelhes, Xiao-Tong Yuan, Bin Gu
2025 A* conf
Query Efficient Black-Box Visual Prompting with Subspace Learning.
CVPR
Zhaogeng Liu, Haozhen Zhang, Hualin Zhang, Xingchen Li, Wanli Shi, Bin Gu, Yi Chang
2025 J jnl
SPACT18: Spiking Human Action Recognition Benchmark Dataset with Complementary RGB and Thermal Modalities.
CoRR
Yasser Ashraf, Ahmed Sharshar, Velibor Bojkovic, Bin Gu
2025 J jnl
Stagewise Training With Exponentially Growing Training Sets.
IEEE Trans. Neural Networks Learn. Syst.
Bin Gu, Hilal AlQuabeh, William de Vazelhes, Zhouyuan Huo, Heng Huang
2025 J jnl
Temporal Misalignment in ANN-SNN Conversion and Its Mitigation via Probabilistic Spiking Neurons.
CoRR
Velibor Bojkovic, Xiaofeng Wu, Bin Gu
2025 A* conf
Temporal Misalignment in ANN-SNN Conversion and its Mitigation via Probabilistic Spiking Neurons.
ICML
Velibor Bojkovic, Xiaofeng Wu, Bin Gu
2024 J jnl
Arabic Dataset for LLM Safeguard Evaluation.
CoRR
Yasser Ashraf, Yuxia Wang, Bin Gu, Preslav Nakov, Timothy Baldwin
2024 J jnl
Asynchronous Parallel Large-Scale Gaussian Process Regression.
IEEE Trans. Neural Networks Learn. Syst.
Zhiyuan Dang, Bin Gu, Cheng Deng, Heng Huang
2024 A* conf
Asynchronous Vertical Federated Learning for Kernelized AUC Maximization.
KDD
Ke Zhang, Ganyu Wang, Han Li, Yulong Wang, Hong Chen, Bin Gu
2024 A* conf
Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks.
ICLR
Bhaskar Mukhoty, Hilal AlQuabeh, Giulia De Masi, Huan Xiong, Bin Gu
2024 J jnl
Continuous Spiking Graph Neural Networks.
CoRR
Nan Yin, Mengzhu Wang, Li Shen, Hitesh Laxmichand Patel, Baopu Li, Bin Gu, Huan Xiong
2024 A* conf
DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption.
ICLR
Nan Yin, Mengzhu Wang, Zhenghan Chen, Li Shen, Huan Xiong, Bin Gu, Xiao Luo
2024 A conf
Data Driven Threshold and Potential Initialization for Spiking Neural Networks.
AISTATS
Velibor Bojkovic, Srinivas Anumasa, Giulia De Masi, Bin Gu, Huan Xiong
2024 A* conf
Double Momentum Method for Lower-Level Constrained Bilevel Optimization.
ICML
Wanli Shi, Yi Chang, Bin Gu
2024 J jnl
Double Momentum Method for Lower-Level Constrained Bilevel Optimization.
CoRR
Wanli Shi, Yi Chang, Bin Gu
2024 A* conf
Dynamic Spiking Graph Neural Networks.
AAAI
Nan Yin, Mengzhu Wang, Zhenghan Chen, Giulia De Masi, Huan Xiong, Bin Gu
2024 J jnl
Dynamic Spiking Graph Neural Networks.
CoRR
Nan Yin, Mengzhu Wang, Zhenghan Chen, Giulia De Masi, Bin Gu, Huan Xiong
2024 A* conf
Enhancing Training of Spiking Neural Network with Stochastic Latency.
AAAI
Srinivas Anumasa, Bhaskar Mukhoty, Velibor Bojkovic, Giulia De Masi, Huan Xiong, Bin Gu
2024 J jnl
Error Density-dependent Empirical Risk Minimization.
Expert Syst. Appl.
Hong Chen, Xuelin Zhang, Tieliang Gong, Bin Gu, Feng Zheng
2024 — conf
Exploring Vulnerabilities in Spiking Neural Networks: Direct Adversarial Attacks on Raw Event Data.
ECCV (72)
Yanmeng Yao, Xiaohan Zhao, Bin Gu
2024 — conf
FTBC: Forward Temporal Bias Correction for Optimizing ANN-SNN Conversion.
ECCV (69)
Xiaofeng Wu, Velibor Bojkovic, Bin Gu, Kun Suo, Kai Zou
2024 J jnl
FTBC: Forward Temporal Bias Correction for Optimizing ANN-SNN Conversion.
CoRR
Xiaofeng Wu, Velibor Bojkovic, Bin Gu, Kun Suo, Kai Zou
2024 A conf
Fast and Adversarial Robust Kernelized SDU Learning.
AISTATS
Yajing Fan, Wanli Shi, Yi Chang, Bin Gu
2024 A* conf
Federated Causal Discovery from Heterogeneous Data.
ICLR
Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
2024 J jnl
Federated Causal Discovery from Heterogeneous Data.
CoRR
Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
2024 A* conf
Fine-grained Analysis of Stability and Generalization for Stochastic Bilevel Optimization.
IJCAI
Xuelin Zhang, Hong Chen, Bin Gu, Tieliang Gong, Feng Zheng
2024 A* conf
General Stability Analysis for Zeroth-Order Optimization Algorithms.
ICLR
Xinyue Liu, Hualin Zhang, Bin Gu, Hong Chen
2024 J jnl
Gradient-Free Method for Heavily Constrained Nonconvex Optimization.
CoRR
Wanli Shi, Hongchang Gao, Bin Gu
2024 A* conf
Hard-Thresholding Meets Evolution Strategies in Reinforcement Learning.
IJCAI
Chengqian Gao, William de Vazelhes, Hualin Zhang, Bin Gu, Zhiqiang Xu
2024 J jnl
Hard-Thresholding Meets Evolution Strategies in Reinforcement Learning.
CoRR
Chengqian Gao, William de Vazelhes, Hualin Zhang, Bin Gu, Zhiqiang Xu
2024 A* conf
How Does Black-Box Impact the Learning Guarantee of Stochastic Compositional Optimization?
NeurIPS
Jun Chen, Hong Chen, Bin Gu
2024 J jnl
Inter-feature Relationship Certifies Robust Generalization of Adversarial Training.
Int. J. Comput. Vis.
Shufei Zhang, Zhuang Qian, Kaizhu Huang, Qiu-Feng Wang, Bin Gu, Huan Xiong, Xinping Yi
2024 J jnl
Is Next Token Prediction Sufficient for GPT? Exploration on Code Logic Comprehension.
CoRR
Mengnan Qi, Yufan Huang, Yongqiang Yao, Maoquan Wang, Bin Gu, Neel Sundaresan
2024 J jnl
Iterative Regularization with k-Support Norm: An Important Complement to Sparse Recovery.
CoRR
William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu
2024 A* conf
Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery.
AAAI
William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu
2024 J jnl
Kernel Path for Semisupervised Support Vector Machine.
IEEE Trans. Neural Networks Learn. Syst.
Zhou Zhai, Heng Huang, Bin Gu
2024 A* conf
Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s).
ICLR
Diyang Li, Charles Ling, Zhiqiang Xu, Huan Xiong, Bin Gu
2024 A conf
Learning Sampling Policy to Achieve Fewer Queries for Zeroth-Order Optimization.
AISTATS
Zhou Zhai, Wanli Shi, Heng Huang, Yi Chang, Bin Gu
2024 A* conf
Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging.
AAAI
Hilal AlQuabeh, William de Vazelhes, Bin Gu
2024 J jnl
Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging.
CoRR
Hilal AlQuabeh, William de Vazelhes, Bin Gu
2024 J jnl
Messages are Never Propagated Alone: Collaborative Hypergraph Neural Network for Time-Series Forecasting.
IEEE Trans. Pattern Anal. Mach. Intell.
Nan Yin, Li Shen, Huan Xiong, Bin Gu, Chong Chen, Xian-Sheng Hua, Siwei Liu, Xiao Luo
2024 A* conf
NDOT: Neuronal Dynamics-based Online Training for Spiking Neural Networks.
ICML
Haiyan Jiang, Giulia De Masi, Huan Xiong, Bin Gu
2024 A* conf
New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions.
ICLR
Xinzhe Yuan, William de Vazelhes, Bin Gu, Huan Xiong
2024 J jnl
New Scalable and Efficient Online Pairwise Learning Algorithm.
IEEE Trans. Neural Networks Learn. Syst.
Bin Gu, Runxue Bao, Chenkang Zhang, Heng Huang
2024 J jnl
Obtaining Lower Query Complexities Through Lightweight Zeroth-Order Proximal Gradient Algorithms.
Neural Comput.
Bin Gu, Xiyuan Wei, Hualin Zhang, Yi Chang, Heng Huang
2024 J jnl
Obtaining Lower Query Complexities through Lightweight Zeroth-Order Proximal Gradient Algorithms.
CoRR
Bin Gu, Xiyuan Wei, Hualin Zhang, Yi Chang, Heng Huang
2024 J jnl
On the Intrinsic Structures of Spiking Neural Networks.
J. Mach. Learn. Res.
Shao-Qun Zhang, Jia-Yi Chen, Jin-Hui Wu, Gao Zhang, Huan Xiong, Bin Gu, Zhi-Hua Zhou
2024 J jnl
On the Number of Linear Regions of Convolutional Neural Networks With Piecewise Linear Activations.
IEEE Trans. Pattern Anal. Mach. Intell.
Huan Xiong, Lei Huang, Wenston J. T. Zang, Xiantong Zhen, Guo-Sen Xie, Bin Gu, Le Song
2024 J jnl
Perturbation diversity certificates robust generalization.
Neural Networks
Zhuang Qian, Shufei Zhang, Kaizhu Huang, Qiufeng Wang, Xinping Yi, Bin Gu, Huan Xiong
2024 J jnl
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization.
Mach. Learn.
Ganyu Wang, Qingsong Zhang, Xiang Li, Boyu Wang, Bin Gu, Charles X. Ling
2024 A* conf
Subspace Selection based Prompt Tuning with Nonconvex Nonsmooth Black-Box Optimization.
KDD
Haozhen Zhang, Hualin Zhang, Bin Gu, Yi Chang
2024 A* conf
TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks.
ICLR
Haiyan Jiang, Vincent Zoonekynd, Giulia De Masi, Bin Gu, Huan Xiong
2024 J jnl
Tackle balancing constraints in semi-supervised ordinal regression.
Mach. Learn.
Chenkang Zhang, Heng Huang, Bin Gu
2023 A* conf
A Unified Optimization Framework of ANN-SNN Conversion: Towards Optimal Mapping from Activation Values to Firing Rates.
ICML
Haiyan Jiang, Srinivas Anumasa, Giulia De Masi, Huan Xiong, Bin Gu
2023 A* conf
A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning.
NeurIPS
Ganyu Wang, Bin Gu, Qingsong Zhang, Xiang Li, Boyu Wang, Charles X. Ling
2023 J jnl
A new large-scale learning algorithm for generalized additive models.
Mach. Learn.
Bin Gu, Chenkang Zhang, Zhouyuan Huo, Heng Huang
2023 A* conf
Accelerated On-Device Forward Neural Network Training with Module-Wise Descending Asynchronism.
NeurIPS
Xiaohan Zhao, Hualin Zhang, Zhouyuan Huo, Bin Gu
2023 J jnl
Advancing Counterfactual Inference through Quantile Regression.
CoRR
Shaoan Xie, Biwei Huang, Bin Gu, Tongliang Liu, Kun Zhang
2023 A* conf
Denoising Multi-Similarity Formulation: A Self-Paced Curriculum-Driven Approach for Robust Metric Learning.
AAAI
Chenkang Zhang, Lei Luo, Bin Gu
2023 A* conf
Direct Training of SNN using Local Zeroth Order Method.
NeurIPS
Bhaskar Mukhoty, Velibor Bojkovic, William de Vazelhes, Xiaohan Zhao, Giulia De Masi, Huan Xiong, Bin Gu
2023 A* conf
Doubly Robust AUC Optimization against Noisy and Adversarial Samples.
KDD
Chenkang Zhang, Wanli Shi, Lei Luo, Bin Gu
2023 J jnl
Energy Efficient Training of SNN using Local Zeroth Order Method.
CoRR
Bhaskar Mukhoty, Velibor Bojkovic, William de Vazelhes, Giulia De Masi, Huan Xiong, Bin Gu
2023 A* conf
Faster Fair Machine via Transferring Fairness Constraints to Virtual Samples.
AAAI
Zhou Zhai, Lei Luo, Heng Huang, Bin Gu
2023 A* conf
Faster Gradient-Free Methods for Escaping Saddle Points.
ICLR
Hualin Zhang, Bin Gu
2023 A* conf
Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization.
NeurIPS
Jun Chen, Hong Chen, Bin Gu, Hao Deng
2023 J jnl
Incremental learning for transductive support vector machine.
Pattern Recognit.
Haiyan Chen, Ying Yu, Yizhen Jia, Bin Gu
2023 J jnl
Kernel Error Path Algorithm.
IEEE Trans. Neural Networks Learn. Syst.
Ziran Xiong, Charles X. Ling, Bin Gu
2023 J jnl
Kernel Path for ν-Support Vector Classification.
IEEE Trans. Neural Networks Learn. Syst.
Bin Gu, Ziran Xiong, Xiang Li, Zhou Zhai, Guansheng Zheng
2023 A conf
On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network.
AISTATS
Hongchang Gao, Bin Gu, My T. Thai
2023 A* conf
On the Stability and Generalization of Triplet Learning.
AAAI
Jun Chen, Hong Chen, Xue Jiang, Bin Gu, Weifu Li, Tieliang Gong, Feng Zheng
2023 J jnl
On the Stability and Generalization of Triplet Learning.
CoRR
Jun Chen, Hong Chen, Xue Jiang, Bin Gu, Weifu Li, Tieliang Gong, Feng Zheng
2023 A* conf
Program Translation via Code Distillation.
EMNLP
Yufan Huang, Mengnan Qi, Yongqiang Yao, Maoquan Wang, Bin Gu, Colin B. Clement, Neel Sundaresan
2023 J jnl
Program Translation via Code Distillation.
CoRR
Yufan Huang, Mengnan Qi, Yongqiang Yao, Maoquan Wang, Bin Gu, Colin B. Clement, Neel Sundaresan
2023 J jnl
Rethinking the Instruction Quality: LIFT is What You Need.
CoRR
Yang Xu, Yongqiang Yao, Yufan Huang, Mengnan Qi, Maoquan Wang, Bin Gu, Neel Sundaresan
2023 A* conf
SUT: Active Defects Probing for Transcompiler Models.
EMNLP
Mengnan Qi, Yufan Huang, Maoquan Wang, Yongqiang Yao, Zihan Liu, Bin Gu, Colin B. Clement, Neel Sundaresan
2023 J jnl
SUT: Active Defects Probing for Transcompiler Models.
CoRR
Mengnan Qi, Yufan Huang, Maoquan Wang, Yongqiang Yao, Zihan Liu, Bin Gu, Colin B. Clement, Neel Sundaresan
2023 J jnl
Secure and Fast Asynchronous Vertical Federated Learning via Cascaded Hybrid Optimization.
CoRR
Ganyu Wang, Qingsong Zhang, Li Xiang, Boyu Wang, Bin Gu, Charles Ling
2023 A* conf
Self-Adaptive Perturbation Radii for Adversarial Training.
KDD
Huimin Wu, Wanli Shi, Chenkang Zhang, Bin Gu
2023 A* conf
Stability-Based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning.
AAAI
Jiahuan Wang, Jun Chen, Hong Chen, Bin Gu, Weifu Li, Xin Tang
2023 J jnl
Stability-based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning.
CoRR
Jiahuan Wang, Jun Chen, Hong Chen, Bin Gu, Weifu Li, Xin Tang
2023 C conf
Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory.
ACML
Hilal AlQuabeh, Bhaskar Mukhoty, Bin Gu
2023 J jnl
Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory.
CoRR
Hilal AlQuabeh, Bhaskar Mukhoty, Bin Gu
2023 A* conf
When Online Learning Meets ODE: Learning without Forgetting on Variable Feature Space.
AAAI
Diyang Li, Bin Gu
2022 A* conf
A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse.
AAAI
Junyi Li, Bin Gu, Heng Huang
2022 A conf
An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification.
CIKM
Runxue Bao, Bin Gu, Heng Huang
2022 J jnl
An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification.
CoRR
Runxue Bao, Bin Gu, Heng Huang
2022 A* conf
Balanced Self-Paced Learning for AUC Maximization.
AAAI
Bin Gu, Chenkang Zhang, Huan Xiong, Heng Huang
2022 J jnl
Balanced Self-Paced Learning for AUC Maximization.
CoRR
Bin Gu, Chenkang Zhang, Huan Xiong, Heng Huang
2022 A* conf
Chunk Dynamic Updating for Group Lasso with ODEs.
AAAI
Diyang Li, Bin Gu
2022 J jnl
Denoising Multi-Similarity Formulation: A Self-paced Curriculum-Driven Approach for Robust Metric Learning.
CoRR
Chenkang Zhang, Lei Luo, Bin Gu
2022 J jnl
Desirable Companion for Vertical Federated Learning: New Zeroth-Order Gradient Based Algorithm.
CoRR
Qingsong Zhang, Bin Gu, Zhiyuan Dang, Cheng Deng, Heng Huang
2022 A* conf
Efficient Semi-Supervised Adversarial Training without Guessing Labels.
ICDM
Huimin Wu, William de Vazelhes, Bin Gu
2022 A* conf
End-to-End Semi-Supervised Ordinal Regression AUC Maximization with Convolutional Kernel Networks.
KDD
Ziran Xiong, Wanli Shi, Bin Gu
2022 A* conf
GAGA: Deciphering Age-path of Generalized Self-paced Regularizer.
NeurIPS
Xingyu Qu, Diyang Li, Xiaohan Zhao, Bin Gu
2022 J jnl
GAGA: Deciphering Age-path of Generalized Self-paced Regularizer.
CoRR
Xingyu Qu, Diyang Li, Xiaohan Zhao, Bin Gu
2022 A* conf
Gradient-Free Method for Heavily Constrained Nonconvex Optimization.
ICML
Wanli Shi, Hongchang Gao, Bin Gu
2022 J jnl
Incremental learning algorithm for large-scale semi-supervised ordinal regression.
Neural Networks
Haiyan Chen, Yizhen Jia, Jiaming Ge, Bin Gu
2022 J jnl
Large-Scale Nonlinear AUC Maximization via Triply Stochastic Gradients.
IEEE Trans. Pattern Anal. Mach. Intell.
Zhiyuan Dang, Xiang Li, Bin Gu, Cheng Deng, Heng Huang
2022 J jnl
Learning to Control under Time-Varying Environment.
CoRR
Yuzhen Han, Ruben Solozabal, Jing Dong, Xingyu Zhou, Martin Takác, Bin Gu
2022 J jnl
Privacy-Preserving Asynchronous Vertical Federated Learning Algorithms for Multiparty Collaborative Learning.
IEEE Trans. Neural Networks Learn. Syst.
Bin Gu, An Xu, Zhouyuan Huo, Cheng Deng, Heng Huang
2022 J jnl
Scaling Up Generalized Kernel Methods.
IEEE Trans. Pattern Anal. Mach. Intell.
Bin Gu, Zhiyuan Dang, Zhouyuan Huo, Cheng Deng, Heng Huang
2022 J jnl
Stochastic Bilevel Distributed Optimization over a Network.
CoRR
Hongchang Gao, Bin Gu, My T. Thai
2022 A* conf
The power of first-order smooth optimization for black-box non-smooth problems.
ICML
Alexander V. Gasnikov, Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takác, Pavel E. Dvurechensky, Bin Gu
2022 A conf
Towards Fairer Classifier via True Fairness Score Path.
CIKM
Bin Gu, Zhou Zhai, Xiang Li, Heng Huang
2022 A conf
Towards Practical Large Scale Non-Linear Semi-Supervised Learning with Balancing Constraints.
CIKM
Zhengqing Gao, Huimin Wu, Martin Takác, Bin Gu
2022 A* conf
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity.
NeurIPS
William de Vazelhes, Hualin Zhang, Huimin Wu, Xiaotong Yuan, Bin Gu
2022 J jnl
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity.
CoRR
William de Vazelhes, Hualin Zhang, Huimin Wu, Xiao-Tong Yuan, Bin Gu
2022 A* conf
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients.
NeurIPS
Hualin Zhang, Huan Xiong, Bin Gu
2022 J jnl
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients.
CoRR
Hualin Zhang, Huan Xiong, Bin Gu
2021 J jnl
A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse.
CoRR
Junyi Li, Bin Gu, Heng Huang
2021 J jnl
A kernel path algorithm for general parametric quadratic programming problem.
Pattern Recognit.
Bin Gu, Ziran Xiong, Shuyang Yu, Guansheng Zheng
2021 J jnl
Accelerating Sequential Minimal Optimization via Stochastic Subgradient Descent.
IEEE Trans. Cybern.
Bin Gu, Yingying Shan, Xin Quan, Guansheng Zheng
2021 J jnl
An Accelerated Variance-Reduced Conditional Gradient Sliding Algorithm for First-order and Zeroth-order Optimization.
CoRR
Xiyuan Wei, Bin Gu, Heng Huang
2021 A* conf
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization.
KDD
Qingsong Zhang, Bin Gu, Cheng Deng, Songxiang Gu, Liefeng Bo, Jian Pei, Heng Huang
2021 J jnl
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization.
CoRR
Qingsong Zhang, Bin Gu, Cheng Deng, Songxiang Gu, Liefeng Bo, Jian Pei, Heng Huang
2021 J jnl
Black-Box Reductions for Zeroth-Order Gradient Algorithms to Achieve Lower Query Complexity.
J. Mach. Learn. Res.
Bin Gu, Xiyuan Wei, Shangqian Gao, Ziran Xiong, Cheng Deng, Heng Huang
2021 A conf
Desirable Companion for Vertical Federated Learning: New Zeroth-Order Gradient Based Algorithm.
CIKM
Qingsong Zhang, Bin Gu, Zhiyuan Dang, Cheng Deng, Heng Huang
2021 J jnl
Efficient Active Learning by Querying Discriminative and Representative Samples and Fully Exploiting Unlabeled Data.
IEEE Trans. Neural Networks Learn. Syst.
Bin Gu, Zhou Zhai, Cheng Deng, Heng Huang
2021 A* conf
Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients.
AAAI
Huimin Wu, Zhengmian Hu, Bin Gu
2021 J jnl
Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients.
CoRR
Huimin Wu, Zhengmian Hu, Bin Gu
2021 A* conf
Finding Age Path of Self-Paced Learning.
ICDM
Bin Gu, Zhou Zhai, Xiang Li, Heng Huang
2021 J jnl
Generalized error path algorithm.
Pattern Recognit.
Bin Gu, Charles X. Ling
2021 A* conf
Improved Penalty Method via Doubly Stochastic Gradients for Bilevel Hyperparameter Optimization.
AAAI
Wanli Shi, Bin Gu
2021 A* conf
Large Batch Optimization for Deep Learning Using New Complete Layer-Wise Adaptive Rate Scaling.
AAAI
Zhouyuan Huo, Bin Gu, Heng Huang
2021 J jnl
Learning Sampling Policy for Faster Derivative Free Optimization.
CoRR
Zhou Zhai, Bin Gu, Heng Huang
2021 J jnl
Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm.
CoRR
Bin Gu, Guodong Liu, Yanfu Zhang, Xiang Geng, Heng Huang
2021 J jnl
Scalable Kernel Ordinal Regression via Doubly Stochastic Gradients.
IEEE Trans. Neural Networks Learn. Syst.
Bin Gu, Xiang Geng, Xiang Li, Wanli Shi, Guansheng Zheng, Cheng Deng, Heng Huang
2021 A* conf
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating.
AAAI
Qingsong Zhang, Bin Gu, Cheng Deng, Heng Huang
2021 J jnl
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating.
CoRR
Qingsong Zhang, Bin Gu, Cheng Deng, Heng Huang
2021 J jnl
Solving large-scale support vector ordinal regression with asynchronous parallel coordinate descent algorithms.
Pattern Recognit.
Bin Gu, Xiang Geng, Wanli Shi, Yingying Shan, Yufang Huang, Zhijie Wang, Guansheng Zheng
2021 J jnl
Triply stochastic gradient method for large-scale nonlinear similar unlabeled classification.
Mach. Learn.
Wanli Shi, Bin Gu, Xiang Li, Cheng Deng, Heng Huang
2020 J jnl
A Unified q-Memorization Framework for Asynchronous Stochastic Optimization.
J. Mach. Learn. Res.
Bin Gu, Wenhan Xian, Zhouyuan Huo, Cheng Deng, Heng Huang
2020 A* conf
Fast OSCAR and OWL Regression via Safe Screening Rules.
ICML
Runxue Bao, Bin Gu, Heng Huang
2020 J jnl
Fast OSCAR and OWL Regression via Safe Screening Rules.
CoRR
Runxue Bao, Bin Gu, Heng Huang
2020 J jnl
Faster On-Device Training Using New Federated Momentum Algorithm.
CoRR
Zhouyuan Huo, Qian Yang, Bin Gu, Lawrence Carin, Heng Huang
2020 A* conf
Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data.
KDD
Bin Gu, Zhiyuan Dang, Xiang Li, Heng Huang
2020 J jnl
Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data.
CoRR
Bin Gu, Zhiyuan Dang, Xiang Li, Heng Huang
2020 J jnl
Improved Bilevel Model: Fast and Optimal Algorithm with Theoretical Guarantee.
CoRR
Junyi Li, Bin Gu, Heng Huang
2020 J jnl
Large Batch Training Does Not Need Warmup.
CoRR
Zhouyuan Huo, Bin Gu, Heng Huang
2020 — ch.
Large-Scale Kernel Method for Vertical Federated Learning.
Federated Learning
Zhiyuan Dang, Bin Gu, Heng Huang
2020 J jnl
Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning.
CoRR
Bin Gu, An Xu, Zhouyuan Huo, Cheng Deng, Heng Huang
2020 A* conf
Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization.
AAAI
Wanli Shi, Bin Gu, Xiang Li, Heng Huang
2020 A* conf
Safe Sample Screening for Robust Support Vector Machine.
AAAI
Zhou Zhai, Bin Gu, Xiang Li, Heng Huang
2020 A* conf
Semi-Supervised Multi-Label Learning from Crowds via Deep Sequential Generative Model.
KDD
Wanli Shi, Victor S. Sheng, Xiang Li, Bin Gu
2019 A* conf
Asynchronous Stochastic Frank-Wolfe Algorithms for Non-Convex Optimization.
IJCAI
Bin Gu, Wenhan Xian, Heng Huang
2019 A* conf
Efficient Approximate Solution Path Algorithm for Order Weight L_1-Norm with Accuracy Guarantee.
ICDM
Runxue Bao, Bin Gu, Heng Huang
2019 J jnl
Efficient inexact proximal gradient algorithms for structured sparsity-inducing norm.
Neural Networks
Bin Gu, Xiang Geng, Xiang Li, Guansheng Zheng
2019 A* conf
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization.
AAAI
Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang
2019 J jnl
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization.
CoRR
Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang
2019 J jnl
Majority Voting and Pairing with Multiple Noisy Labeling.
IEEE Trans. Knowl. Data Eng.
Victor S. Sheng, Jing Zhang, Bin Gu, Xindong Wu
2019 J jnl
Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization.
CoRR
Wanli Shi, Bin Gu, Xiang Li, Heng Huang
2019 A* conf
Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization.
IJCAI
Wanli Shi, Bin Gu, Xiang Li, Xiang Geng, Heng Huang
2019 J jnl
Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization.
CoRR
Wanli Shi, Bin Gu, Xiang Li, Xiang Geng, Heng Huang
2019 J jnl
Safe Sample Screening for Robust Support Vector Machine.
CoRR
Zhou Zhai, Bin Gu, Xiang Li, Heng Huang
2019 A* conf
Scalable Semi-Supervised SVM via Triply Stochastic Gradients.
IJCAI
Xiang Geng, Bin Gu, Xiang Li, Wanli Shi, Guansheng Zheng, Heng Huang
2019 J jnl
Scalable Semi-Supervised SVM via Triply Stochastic Gradients.
CoRR
Xiang Geng, Bin Gu, Xiang Li, Wanli Shi, Guansheng Zheng, Heng Huang
2019 A* conf
Scalable and Efficient Pairwise Learning to Achieve Statistical Accuracy.
AAAI
Bin Gu, Zhouyuan Huo, Heng Huang
2019 A* conf
Tackle Balancing Constraint for Incremental Semi-Supervised Support Vector Learning.
KDD
Shuyang Yu, Bin Gu, Kunpeng Ning, Haiyan Chen, Jian Pei, Heng Huang
2018 J jnl
A Solution Path Algorithm for General Parametric Quadratic Programming Problem.
IEEE Trans. Neural Networks Learn. Syst.
Bin Gu, Victor S. Sheng
2018 J jnl
A regularization path algorithm for support vector ordinal regression.
Neural Networks
Bin Gu
2018 A* conf
Accelerated Asynchronous Greedy Coordinate Descent Algorithm for SVMs.
IJCAI
Bin Gu, Yingying Shan, Xiang Geng, Guansheng Zheng
2018 A* conf
Accelerated Method for Stochastic Composition Optimization With Nonsmooth Regularization.
AAAI
Zhouyuan Huo, Bin Gu, Ji Liu, Heng Huang
2018 A conf
Asynchronous Doubly Stochastic Group Regularized Learning.
AISTATS
Bin Gu, Zhouyuan Huo, Heng Huang
2018 A* conf
Asynchronous Doubly Stochastic Sparse Kernel Learning.
AAAI
Bin Gu, Miao Xin, Zhouyuan Huo, Heng Huang
2018 J jnl
Chunk incremental learning for cost-sensitive hinge loss support vector machine.
Pattern Recognit.
Bin Gu, Xin Quan, Yunhua Gu, Victor S. Sheng, Guansheng Zheng
2018 A* conf
Decoupled Parallel Backpropagation with Convergence Guarantee.
ICML
Zhouyuan Huo, Bin Gu, Qian Yang, Heng Huang
2018 J jnl
Decoupled Parallel Backpropagation with Convergence Guarantee.
CoRR
Zhouyuan Huo, Bin Gu, Qian Yang, Heng Huang
2018 A* conf
Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines.
ICML
Bin Gu, Zhouyuan Huo, Cheng Deng, Heng Huang
2018 A* conf
Faster Training Algorithms for Structured Sparsity-Inducing Norm.
IJCAI
Bin Gu, Xingwang Ju, Xiang Li, Guansheng Zheng
2018 A* conf
Inexact Proximal Gradient Methods for Non-Convex and Non-Smooth Optimization.
AAAI
Bin Gu, De Wang, Zhouyuan Huo, Heng Huang
2018 A* conf
New Incremental Learning Algorithm for Semi-Supervised Support Vector Machine.
KDD
Bin Gu, Xiao-Tong Yuan, Songcan Chen, Heng Huang
2018 J jnl
Sparse regression with output correlation for cardiac ejection fraction estimation.
Inf. Sci.
Bin Gu, Yingying Shan, Victor S. Sheng, Yuhui Zheng, Shuo Li
2018 J jnl
The convergence of linear classifiers on large sparse data.
Neurocomputing
Xiang Li, Huaimin Wang, Bin Gu, Charles X. Ling
2018 A* conf
Training Neural Networks Using Features Replay.
NeurIPS
Zhouyuan Huo, Bin Gu, Heng Huang
2018 J jnl
Training Neural Networks Using Features Replay.
CoRR
Zhouyuan Huo, Bin Gu, Heng Huang
2017 J jnl
A Robust Regularization Path Algorithm for ν-Support Vector Classification.
IEEE Trans. Neural Networks Learn. Syst.
Bin Gu, Victor S. Sheng
2017 J jnl
Accelerated Method for Stochastic Composition Optimization with Nonsmooth Regularization.
CoRR
Zhouyuan Huo, Bin Gu, Heng Huang
2017 J jnl
Cross Validation Through Two-Dimensional Solution Surface for Cost-Sensitive SVM.
IEEE Trans. Pattern Anal. Mach. Intell.
Bin Gu, Victor S. Sheng, KengYeow Tay, Walter Romano, Shuo Li
2017 A* conf
Groups-Keeping Solution Path Algorithm for Sparse Regression with Automatic Feature Grouping.
KDD
Bin Gu, Guodong Liu, Heng Huang
2017 J jnl
Structural Minimax Probability Machine.
IEEE Trans. Neural Networks Learn. Syst.
Bin Gu, Xingming Sun, Victor S. Sheng
2017 A conf
Triply Stochastic Gradients on Multiple Kernel Learning.
UAI
Xiang Li, Bin Gu, Shuang Ao, Huaimin Wang, Charles X. Ling
2016 J jnl
Asynchronous Doubly Stochastic Proximal Optimization with Variance Reduction.
CoRR
Bin Gu, Zhouyuan Huo, Heng Huang
2016 J jnl
Decoupled Asynchronous Proximal Stochastic Gradient Descent with Variance Reduction.
CoRR
Zhouyuan Huo, Bin Gu, Heng Huang
2016 J jnl
Inexact Proximal Gradient Methods for Non-convex and Non-smooth Optimization.
CoRR
Bin Gu, Zhouyuan Huo, Heng Huang
2016 J jnl
Zeroth-order Asynchronous Doubly Stochastic Algorithm with Variance Reduction.
CoRR
Bin Gu, Zhouyuan Huo, Heng Huang
2015 A* conf
A New Generalized Error Path Algorithm for Model Selection.
ICML
Bin Gu, Charles X. Ling
2015 A* conf
Bi-Parameter Space Partition for Cost-Sensitive SVM.
IJCAI
Bin Gu, Victor S. Sheng, Shuo Li
2015 A* conf
Data Sparseness in Linear SVM.
IJCAI
Xiang Li, Huaimin Wang, Bin Gu, Charles X. Ling
2015 J jnl
Incremental Support Vector Learning for Ordinal Regression.
IEEE Trans. Neural Networks Learn. Syst.
Bin Gu, Victor S. Sheng, KengYeow Tay, Walter Romano, Shuo Li
2015 J jnl
Incremental learning for ν-Support Vector Regression.
Neural Networks
Bin Gu, Victor S. Sheng, Zhijie Wang, Derek Ho, Said Osman, Shuo Li
2014 J jnl
Cost-sensitive learning for defect escalation.
Knowl. Based Syst.
Victor S. Sheng, Bin Gu, Wei Fang, Jian Wu
2014 J jnl
Direct Estimation of Cardiac Biventricular Volumes With an Adapted Bayesian Formulation.
IEEE Trans. Biomed. Eng.
Zhijie Wang, Mohamed Ben Salah, Bin Gu, Ali Islam, Aashish Goela, Shuo Li
2013 J jnl
Feasibility and Finite Convergence Analysis for Accurate On-Line $\nu$-Support Vector Machine.
IEEE Trans. Neural Networks Learn. Syst.
Bin Gu, Victor S. Sheng
2012 J jnl
Accurate on-line v-support vector learning.
Neural Networks
Bin Gu, Jiandong Wang, Yuecheng Yu, Guansheng Zheng, Yufan Huang, Tao Xu
2012 J jnl
Regularization Path for ν-Support Vector Classification.
IEEE Trans. Neural Networks Learn. Syst.
Bin Gu, Jiandong Wang, Guansheng Zheng, Yuecheng Yu
2010 J jnl
Ordinal-Class Core Vector Machine.
J. Comput. Sci. Technol.
Bin Gu, Jiandong Wang, Tao Li
2010 J jnl
Semi-supervised Distributed Clustering with Mahalanobis Distance Metric Learning.
J. Digit. Content Technol. its Appl.
Yuecheng Yu, Jiandong Wang, Guansheng Zheng, Bin Gu
2008 B conf
On-line off-line Ranking Support Vector Machine and analysis.
IJCNN
Bin Gu, Jiandong Wang, Haiyan Chen