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Bin Gu

91 papers · 2015–2026 · 15 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (22) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (9) πŸƒ Academic Marathon (10) 🌍 Conference Polyglot (15) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🏠 Conference Loyalist (22) πŸ† Keyword Champion (3) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ‘₯ Mega-Team (20) πŸ”¬ Deep Specialist (24) 🀝 Dynamic Duo (20) πŸš€ Conference Pioneer ⚑ Prolific Year (16) πŸ”₯ Unstoppable (8) πŸ—ƒοΈ Keyword Collector (73) πŸ’Ž Century Club (90) πŸ“ˆ Trend Setter ❓ The Questioner

Conferences

AAAI (23) ICML (12) ICLR (11) IJCAI (9) NIPS (9) INTERSPEECH (8) AISTATS (5) ACL (3) JMLR (3) ECCV (2) EMNLP (2) ACML (1) COLING (1) CVPR (1) NAACL (1)

Top co-authors

Heng Huang (20) Huan Xiong (14) Wanli Shi (9) Zhouyuan Huo (9) Giulia De Masi (8) Hualin Zhang (8) Hong Chen (7) William de Vazelhes (7) Wu Guo (7) Xiang Li (7)

Research topics

Core AI (1)

Keywords

stochastic optimization (8) stochastic gradient descent (6) pairwise learning (6) zeroth-order optimization (6) spiking neural network (6) stochastic gradient (5) kernel methods (5) speaker verification (5) auc maximization (5) large language model (5) generalization bound (4) support vector machine (4) convergence rate (4) variance reduction (4) black-box optimization (4) bilevel optimization (4) convergence guarantee (4) group lasso (3) neural network optimization (3) speaker embedding (3)

Papers

Towards Nonlinear Sparse AUC Maximization via Compositional Stochastic Hard Thresholding AAAI 2026
Improving Generalization and Robustness in SNNs Through Signed Rate Encoding and Sparse Encoding Attacks ICLR 2025
Collaborative Discrete-Continuous Black-Box Prompt Learning for Language Models ICLR 2025
Event-Driven Online Vertical Federated Learning ICLR 2025
Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent AAAI 2025
Leveraging First and Zeroth-Order Gradient to Address Imbalanced Black-Box Prompt Tuning via Minimax Optimization AAAI 2025
Arabic Dataset for LLM Safeguard Evaluation NAACL 2025
FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning ICML 2025
Rethinking Repetition Problems of LLMs in Code Generation ACL 2025
Temporal Misalignment in ANN-SNN Conversion and its Mitigation via Probabilistic Spiking Neurons ICML 2025
Optimization over Sparse Support-Preserving Sets: Two-Step Projection with Global Optimality Guarantees ICML 2025
Query Efficient Black-Box Visual Prompting with Subspace Learning CVPR 2025
NDOT: Neuronal Dynamics-based Online Training for Spiking Neural Networks ICML 2024
On the Intrinsic Structures of Spiking Neural Networks JMLR 2024
How Does Black-Box Impact the Learning Guarantee of Stochastic Compositional Optimization? NIPS 2024
Contrastive Learning and Inter-Speaker Distribution Alignment Based Unsupervised Domain Adaptation for Robust Speaker Verification INTERSPEECH 2024
Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging AAAI 2024
Enhancing Training of Spiking Neural Network with Stochastic Latency AAAI 2024
Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery AAAI 2024
Dynamic Spiking Graph Neural Networks AAAI 2024
DevEval: A Manually-Annotated Code Generation Benchmark Aligned with Real-World Code Repositories ACL 2024
Generalization or Memorization: Data Contamination and Trustworthy Evaluation for Large Language Models ACL 2024
Fine-grained Analysis of Stability and Generalization for Stochastic Bilevel Optimization IJCAI 2024
Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s) ICLR 2024
Fast and Adversarial Robust Kernelized SDU Learning AISTATS 2024
Hard-Thresholding Meets Evolution Strategies in Reinforcement Learning IJCAI 2024
Learning Sampling Policy to Achieve Fewer Queries for Zeroth-Order Optimization AISTATS 2024
Data Driven Threshold and Potential Initialization for Spiking Neural Networks AISTATS 2024
New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions ICLR 2024
FTBC: Forward Temporal Bias Correction for Optimizing ANN-SNN Conversion ECCV 2024
Exploring Vulnerabilities in Spiking Neural Networks: Direct Adversarial Attacks on Raw Event Data ECCV 2024
Federated Causal Discovery from Heterogeneous Data ICLR 2024
Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks ICLR 2024
DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption ICLR 2024
TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks ICLR 2024
General Stability Analysis for Zeroth-Order Optimization Algorithms ICLR 2024
Double Momentum Method for Lower-Level Constrained Bilevel Optimization ICML 2024
SUT: Active Defects Probing for Transcompiler Models EMNLP 2023
A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning NIPS 2023
Direct Training of SNN using Local Zeroth Order Method NIPS 2023
Accelerated On-Device Forward Neural Network Training with Module-Wise Descending Asynchronism NIPS 2023
Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization NIPS 2023
On the Stability and Generalization of Triplet Learning AAAI 2023
When Online Learning Meets ODE: Learning without Forgetting on Variable Feature Space AAAI 2023
Stability-Based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning AAAI 2023
Denoising Multi-Similarity Formulation: A Self-Paced Curriculum-Driven Approach for Robust Metric Learning AAAI 2023
Faster Fair Machine via Transferring Fairness Constraints to Virtual Samples AAAI 2023
Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory ACML 2023
On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network AISTATS 2023
Program Translation via Code Distillation EMNLP 2023
Faster Gradient-Free Methods for Escaping Saddle Points ICLR 2023
A Unified Optimization Framework of ANN-SNN Conversion: Towards Optimal Mapping from Activation Values to Firing Rates ICML 2023
Introducing Self-Supervised Phonetic Information for Text-Independent Speaker Verification INTERSPEECH 2023
Gradient-Free Method for Heavily Constrained Nonconvex Optimization ICML 2022
Deep speaker embedding with frame-constrained training strategy for speaker verification INTERSPEECH 2022
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity NIPS 2022
Balanced Self-Paced Learning for AUC Maximization AAAI 2022
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients NIPS 2022
A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse AAAI 2022
Chunk Dynamic Updating for Group Lasso with ODEs AAAI 2022
GAGA: Deciphering Age-path of Generalized Self-paced Regularizer NIPS 2022
The power of first-order smooth optimization for black-box non-smooth problems ICML 2022
Bidirectional Multiscale Feature Aggregation for Speaker Verification INTERSPEECH 2021
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating AAAI 2021
Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients AAAI 2021
Improved Penalty Method via Doubly Stochastic Gradients for Bilevel Hyperparameter Optimization AAAI 2021
Large Batch Optimization for Deep Learning Using New Complete Layer-Wise Adaptive Rate Scaling AAAI 2021
Black-Box Reductions for Zeroth-Order Gradient Algorithms to Achieve Lower Query Complexity JMLR 2021
Improved Meta-Learning Training for Speaker Verification INTERSPEECH 2021
A Unified q-Memorization Framework for Asynchronous Stochastic Optimization JMLR 2020
An Adaptive X-Vector Model for Text-Independent Speaker Verification INTERSPEECH 2020
Fast OSCAR and OWL Regression via Safe Screening Rules ICML 2020
Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization AAAI 2020
Unsupervised Regularization-Based Adaptive Training for Speech Recognition INTERSPEECH 2020
Adaptive Speaker Normalization for CTC-Based Speech Recognition INTERSPEECH 2020
Safe Sample Screening for Robust Support Vector Machine AAAI 2020
Graph-based Aspect Representation Learning for Entity Resolution COLING 2020
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization AAAI 2019
Scalable and Efficient Pairwise Learning to Achieve Statistical Accuracy AAAI 2019
Asynchronous Stochastic Frank-Wolfe Algorithms for Non-Convex Optimization IJCAI 2019
Scalable Semi-Supervised SVM via Triply Stochastic Gradients IJCAI 2019
Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization IJCAI 2019
Accelerated Asynchronous Greedy Coordinate Descent Algorithm for SVMs IJCAI 2018
Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines ICML 2018
Decoupled Parallel Backpropagation with Convergence Guarantee ICML 2018
Faster Training Algorithms for Structured Sparsity-Inducing Norm IJCAI 2018
Asynchronous Doubly Stochastic Group Regularized Learning AISTATS 2018
Training Neural Networks Using Features Replay NIPS 2018
Bi-Parameter Space Partition for Cost-Sensitive SVM IJCAI 2015
A New Generalized Error Path Algorithm for Model Selection ICML 2015
Data Sparseness in Linear SVM IJCAI 2015