Bin Gu

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