Heng Huang

Asymmetric Conflict and Synergy in Post-training for LLM-based Multilingual Machine Translation ACL 2025 Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models CVPR 2025 LLaVA-Critic: Learning to Evaluate Multimodal Models CVPR 2025 SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models CVPR 2025 Identification of Intermittent Temporal Latent Process ICLR 2025 A Watermark for Order-Agnostic Language Models ICLR 2025 Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models ICLR 2025 OmnixR: Evaluating Omni-modality Language Models on Reasoning across Modalities ICLR 2025 Escaping Saddle Point Efficiently in Minimax and Bilevel Optimizations IJCAI 2025 Revisiting Convergence: Shuffling Complexity Beyond Lipschitz Smoothness ICML 2025 De-mark: Watermark Removal in Large Language Models ICML 2025 Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations ICLR 2025 Towards Optimal Multi-draft Speculative Decoding ICLR 2025 ARGUS: Hallucination and Omission Evaluation in Video-LLMs ICCV 2025 Federated Continuous Category Discovery and Learning ICCV 2025 GenFlowRL: Shaping Rewards with Generative Object-Centric Flow in Visual Reinforcement Learning ICCV 2025 Web Intellectual Property at Risk: Preventing Unauthorized Real-Time Retrieval by Large Language Models EMNLP 2025 Improved Unbiased Watermark for Large Language Models ACL 2025 From Lists to Emojis: How Format Bias Affects Model Alignment ACL 2025 A Resilient and Accessible Distribution-Preserving Watermark for Large Language Models ICML 2024 Paintings and Drawings Aesthetics Assessment with Rich Attributes for Various Artistic Categories IJCAI 2024 Revisiting Adaptive Cellular Recognition Under Domain Shifts: A Contextual Correspondence View ECCV 2024 Defense against Model Extraction Attack by Bayesian Active Watermarking ICML 2024 Retrieval Across Any Domains via Large-scale Pre-trained Model ICML 2024 Delving into the Convergence of Generalized Smooth Minimax Optimization ICML 2024 Robust Reinforcement Learning with General Utility NIPS 2024 Inevitable Trade-off between Watermark Strength and Speculative Sampling Efficiency for Language Models NIPS 2024 Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling NIPS 2024 APDDv2: Aesthetics of Paintings and Drawings Dataset with Artist Labeled Scores and Comments NIPS 2024 ZeroMark: Towards Dataset Ownership Verification without Disclosing Watermark NIPS 2024 Model Sensitivity Aware Continual Learning NIPS 2024 Event3DGS: Event-Based 3D Gaussian Splatting for High-Speed Robot Egomotion CORL 2024 Accelerated Speculative Sampling Based on Tree Monte Carlo ICML 2024 ODIN: Disentangled Reward Mitigates Hacking in RLHF ICML 2024 Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation ICLR 2024 AlpaGasus: Training a Better Alpaca with Fewer Data ICLR 2024 A Unified and General Framework for Continual Learning ICLR 2024 On the Hardness of Constrained Cooperative Multi-Agent Reinforcement Learning ICLR 2024 Unbiased Watermark for Large Language Models ICLR 2024 Dropout Enhanced Bilevel Training ICLR 2024 Mixture of Efficient Diffusion Experts Through Automatic Interval and Sub-Network Selection ECCV 2024 Learning Sampling Policy to Achieve Fewer Queries for Zeroth-Order Optimization AISTATS 2024 Prompting Language-Informed Distribution for Compositional Zero-Shot Learning ECCV 2024 FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization ICLR 2024 Compressing Image-to-Image Translation GANs Using Local Density Structures on Their Learned Manifold AAAI 2024 On the Role of Server Momentum in Federated Learning AAAI 2024 BilevelPruning: Unified Dynamic and Static Channel Pruning for Convolutional Neural Networks CVPR 2024 Jointly Training and Pruning CNNs via Learnable Agent Guidance and Alignment CVPR 2024 Device-Wise Federated Network Pruning CVPR 2024 Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch CVPR 2024 Seeing Unseen: Discover Novel Biomedical Concepts via Geometry-Constrained Probabilistic Modeling CVPR 2024 Accelerated Policy Gradient for s-rectangular Robust MDPs with Large State Spaces ICML 2024 InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models ICML 2024 Adversarial Fairness Network AAAI 2024 Your Vision-Language Model Itself Is a Strong Filter: Towards High-Quality Instruction Tuning with Data Selection ACL 2024 A Bayesian Approach to Harnessing the Power of LLMs in Authorship Attribution EMNLP 2024 Few-shot Class Incremental Learning with Attention-Aware Self-Adaptive Prompt ECCV 2024 Interpretable Spatio-Temporal Embedding for Brain Structural-Effective Network with Ordinary Differential Equation MICCAI 2024 Decentralized Riemannian Algorithm for Nonconvex Minimax Problems AAAI 2023 Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems NIPS 2023 Resolving the Tug-of-War: A Separation of Communication and Learning in Federated Learning NIPS 2023 Federated Conditional Stochastic Optimization NIPS 2023 Solving a Class of Non-Convex Minimax Optimization in Federated Learning NIPS 2023 Optimization and Bayes: A Trade-off for Overparameterized Neural Networks NIPS 2023 Domain Watermark: Effective and Harmless Dataset Copyright Protection is Closed at Hand NIPS 2023 Finding Local Minima Efficiently in Decentralized Optimization NIPS 2023 EffConv: Efficient Learning of Kernel Sizes for Convolution Layers of CNNs AAAI 2023 Faster Adaptive Federated Learning AAAI 2023 Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks AAAI 2023 Faster Fair Machine via Transferring Fairness Constraints to Virtual Samples AAAI 2023 Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets CVPR 2023 PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer EMNLP 2023 Taxonomy Adaptive Cross-Domain Adaptation in Medical Imaging via Optimization Trajectory Distillation ICCV 2023 Learning with Diversity: Self-Expanded Equalization for Better Generalized Deep Metric Learning ICCV 2023 Structural Alignment for Network Pruning through Partial Regularization ICCV 2023 Learning to Jointly Share and Prune Weights for Grounding Based Vision and Language Models ICLR 2023 Tighter Analysis for ProxSkip ICML 2023 Beyond Lipschitz Smoothness: A Tighter Analysis for Nonconvex Optimization ICML 2023 A Law of Robustness beyond Isoperimetry ICML 2023 Detached Error Feedback for Distributed SGD with Random Sparsification ICML 2022 A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse AAAI 2022 Balanced Self-Paced Learning for AUC Maximization AAAI 2022 Doubly Sparse Asynchronous Learning for Stochastic Composite Optimization IJCAI 2022 Enhanced Bilevel Optimization via Bregman Distance NIPS 2022 MetricFormer: A Unified Perspective of Correlation Exploring in Similarity Learning NIPS 2022 Noise Is Also Useful: Negative Correlation-Steered Latent Contrastive Learning CVPR 2022 On the Convergence of Local Stochastic Compositional Gradient Descent with Momentum ICML 2022 Closing the Generalization Gap of Cross-Silo Federated Medical Image Segmentation CVPR 2022 Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization JMLR 2022 Disentangled Differentiable Network Pruning ECCV 2022 Recover Fair Deep Classification Models via Altering Pre-trained Structure ECCV 2022 Interpretations Steered Network Pruning via Amortized Inferred Saliency Maps ECCV 2022 RetrievalGuard: Provably Robust 1-Nearest Neighbor Image Retrieval ICML 2022 Bregman Gradient Policy Optimization ICLR 2022 Learning Universal Adversarial Perturbation by Adversarial Example AAAI 2022 Coordinating Momenta for Cross-Silo Federated Learning AAAI 2022 Fast Training Method for Stochastic Compositional Optimization Problems NIPS 2021 On the Random Conjugate Kernel and Neural Tangent Kernel ICML 2021 Network Pruning via Performance Maximization CVPR 2021 Unsupervised Hyperbolic Metric Learning CVPR 2021 SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients NIPS 2021 Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems NIPS 2021 Optimal Underdamped Langevin MCMC Method NIPS 2021 Learning Better Visual Data Similarities via New Grouplet Non-Euclidean Embedding ICCV 2021 Adversarial Attack on Deep Cross-Modal Hamming Retrieval ICCV 2021 Exploration and Estimation for Model Compression ICCV 2021 Black-Box Reductions for Zeroth-Order Gradient Algorithms to Achieve Lower Query Complexity JMLR 2021 Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating AAAI 2021 Step-Ahead Error Feedback for Distributed Training with Compressed Gradient AAAI 2021 Communication-Efficient Frank-Wolfe Algorithm for Nonconvex Decentralized Distributed Learning AAAI 2021 Large Batch Optimization for Deep Learning Using New Complete Layer-Wise Adaptive Rate Scaling AAAI 2021 On the Convergence of Communication-Efficient Local SGD for Federated Learning AAAI 2021 Nearest Neighbor Matching for Deep Clustering CVPR 2021 A Faster Decentralized Algorithm for Nonconvex Minimax Problems NIPS 2021 Multi-Scale Fusion Subspace Clustering Using Similarity Constraint CVPR 2020 Sinkhorn Regression IJCAI 2020 Discrete Model Compression With Resource Constraint for Deep Neural Networks CVPR 2020 Fast OSCAR and OWL Regression via Safe Screening Rules ICML 2020 Adversarial Nonnegative Matrix Factorization ICML 2020 Momentum-Based Policy Gradient Methods ICML 2020 Sparse Shrunk Additive Models ICML 2020 Safe Sample Screening for Robust Support Vector Machine AAAI 2020 Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization AAAI 2020 On the Acceleration of Deep Learning Model Parallelism With Staleness CVPR 2020 A Unified q-Memorization Framework for Asynchronous Stochastic Optimization JMLR 2020 Towards Transferable Targeted Attack CVPR 2020 Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-Weighting CVPR 2020 Binarized Neural Network for Single Image Super Resolution ECCV 2020 Can Stochastic Zeroth-Order Frank-Wolfe Method Converge Faster for Non-Convex Problems? ICML 2020 Asynchronous Stochastic Frank-Wolfe Algorithms for Non-Convex Optimization IJCAI 2019 Cross Domain Model Compression by Structurally Weight Sharing CVPR 2019 Balanced Self-Paced Learning for Generative Adversarial Clustering Network CVPR 2019 Heterogeneous Memory Enhanced Multimodal Attention Model for Video Question Answering CVPR 2019 Robust Metric Learning on Grassmann Manifolds with Generalization Guarantees AAAI 2019 Orthogonality-Promoting Dictionary Learning via Bayesian Inference AAAI 2019 Scalable and Efficient Pairwise Learning to Achieve Statistical Accuracy AAAI 2019 Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization AAAI 2019 Demystifying Dropout ICML 2019 Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization ICML 2019 Curvilinear Distance Metric Learning NIPS 2019 Binarized Neural Networks for Resource-Efficient Hashing with Minimizing Quantization Loss IJCAI 2019 Scalable Semi-Supervised SVM via Triply Stochastic Gradients IJCAI 2019 Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization IJCAI 2019 Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization IJCAI 2019 Joint Generative Moment-Matching Network for Learning Structural Latent Code IJCAI 2018 Unsupervised Deep Generative Adversarial Hashing Network CVPR 2018 Training Neural Networks Using Features Replay NIPS 2018 Bilevel Distance Metric Learning for Robust Image Recognition NIPS 2018 Asynchronous Doubly Stochastic Group Regularized Learning AISTATS 2018 Fast Vehicle Identification in Surveillance via Ranked Semantic Sampling Based Embedding IJCAI 2018 Deep Attributed Network Embedding IJCAI 2018 Multi-Level Metric Learning via Smoothed Wasserstein Distance IJCAI 2018 New Balanced Active Learning Model and Optimization Algorithm IJCAI 2018 Stochastic Second-Order Method for Large-Scale Nonconvex Sparse Learning Models IJCAI 2018 Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines ICML 2018 Decoupled Parallel Backpropagation with Convergence Guarantee ICML 2018 Direct Shape Regression Networks for End-to-End Face Alignment CVPR 2018 Multi-Class Support Vector Machine via Maximizing Multi-Class Margins IJCAI 2017 Joint Capped Norms Minimization for Robust Matrix Recovery IJCAI 2017 Learning A Structured Optimal Bipartite Graph for Co-Clustering NIPS 2017 Theoretic Analysis and Extremely Easy Algorithms for Domain Adaptive Feature Learning IJCAI 2017 Predicting Alzheimer's Disease Cognitive Assessment via Robust Low-Rank Structured Sparse Model IJCAI 2017 Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization ICCV 2017 Locally-Transferred Fisher Vectors for Texture Classification ICCV 2017 Regularized Modal Regression with Applications in Cognitive Impairment Prediction NIPS 2017 Group Sparse Additive Machine NIPS 2017 Fast Robust Non-Negative Matrix Factorization for Large-Scale Human Action Data Clustering IJCAI 2016 UTA DLNLP at SemEval-2016 Task 1: Semantic Textual Similarity: A Unified Framework for Semantic Processing and Evaluation SEMEVAL 2016 UTA DLNLP at SemEval-2016 Task 12: Deep Learning Based Natural Language Processing System for Clinical Information Identification from Clinical Notes and Pathology Reports SEMEVAL 2016 Error Analysis of Generalized Nyström Kernel Regression NIPS 2016 Subspace Clustering via New Low-Rank Model with Discrete Group Structure Constraint IJCAI 2016 Fusing Subcategory Probabilities for Texture Classification CVPR 2015 Discriminative Unsupervised Dimensionality Reduction IJCAI 2015 Robust Dictionary Learning with Capped l1-Norm IJCAI 2015 A New Simplex Sparse Learning Model to Measure Data Similarity for Clustering IJCAI 2015 Multi-View Subspace Clustering ICCV 2015 Linear Time Solver for Primal SVM ICML 2014 Video Motion Segmentation Using New Adaptive Manifold Denoising Model CVPR 2014 Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization ICML 2014 Optimal Mean Robust Principal Component Analysis ICML 2014 Exact Top-k Feature Selection via l2,0-Norm Constraint IJCAI 2013 New Graph Structured Sparsity Model for Multi-label Image Annotations ICCV 2013 Multi-View Clustering and Feature Learning via Structured Sparsity ICML 2013 Multi-View K-Means Clustering on Big Data IJCAI 2013 Heterogeneous Visual Features Fusion via Sparse Multimodal Machine CVPR 2013 Social Trust Prediction Using Rank-k Matrix Recovery IJCAI 2013 Semi-supervised Robust Dictionary Learning via Efficient l-Norms Minimization ICCV 2013 Heterogeneous Image Features Integration via Multi-modal Semi-supervised Learning Model ICCV 2013 Robust and Discriminative Self-Taught Learning ICML 2013 Protein Function Prediction via Laplacian Network Partitioning Incorporating Function Category Correlations IJCAI 2013 Early Active Learning via Robust Representation and Structured Sparsity IJCAI 2013 Adaptive Loss Minimization for Semi-Supervised Elastic Embedding IJCAI 2013 Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach NIPS 2012 High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction NIPS 2012 Maximum Margin Multi-Instance Learning NIPS 2011 Efficient and Robust Feature Selection via Joint ℓ2,1-Norms Minimization NIPS 2010