Heng Huang

发表

Asynchronous Stochastic Block Coordinate Descent with Variance Reduction

Bin Gu, Heng Huang, Zhouyuan Huo, 2016, 1610.09447.

Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization pdf

Bin Gu, Feihu Huang, Songcan Chen, 2019, AAAI.

Asynchronous Stochastic Gradient Descent with Variance Reduction for Non-Convex Optimization pdf

Heng Huang, Zhouyuan Huo, Zhouyuan Huo, 2016, AAAI 2016.

Predicting Alzheimer's Disease Cognitive Assessment via Robust Low-Rank Structured Sparse Model

Dinggang Shen, Jie Xu, Heng Huang, 2017, IJCAI.

Cognitive Assessment Prediction in Alzheimer’s Disease by Multi-Layer Multi-Target Regression

Dinggang Shen, Heng Huang, Xiantong Zhen, 2018, Neuroinformatics.

EXPLOIT WHERE OPTIMIZER EXPLORES

Zhouyuan Huo, Heng Huang, 2020 .

Decoupled Parallel Backpropagation with Convergence Guarantee

Bin Gu, Heng Huang, Qian Yang, 2018, ICML.

Distributed Dynamic Safe Screening Algorithms for Sparse Regularization

Heng Huang, R. Bao, Xidong Wu, 2022, 2204.10981.

Appendix for Paper “ Asynchronous Doubly Stochastic Group Regularized Learning ”

Zhouyuan Huo, Bin Gu, Heng Huang, 2018 .

Temporal Correlation Structure Learning for MCI Conversion Prediction

Dinggang Shen, Heng Huang, Weidong Cai, 2018, MICCAI.

Enhanced Bilevel Optimization via Bregman Distance

Heng Huang, Feihu Huang, 2021, ArXiv.

SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients

Heng Huang, Feihu Huang, Junyi Li, 2021, NeurIPS.

Detached Error Feedback for Distributed SGD with Random Sparsification

Heng Huang, An Xu, 2020, ICML.

Robust Self-Supervised Structural Graph Neural Network for Social Network Prediction

Heng Huang, Hongchang Gao, Yanfu Zhang, 2022, WWW.

Balanced Self-Paced Learning for AUC Maximization

Bin Gu, Heng Huang, H. Xiong, 2022, AAAI.

Interpretations Steered Network Pruning via Amortized Inferred Saliency Maps

Heng Huang, Shangqian Gao, A. Ganjdanesh, 2022, ECCV.

Improving Social Network Embedding via New Second-Order Continuous Graph Neural Networks

Heng Huang, Yanfu Zhang, Shangqian Gao, 2022, KDD.

Doubly Sparse Asynchronous Learning for Stochastic Composite Optimization

Heng Huang, R. Bao, Xidong Wu, 2022, IJCAI.

Enhanced Bilevel Optimization via Bregman Distance

Heng Huang, Feihu Huang, Junyi Li, 2021, NeurIPS.

Noise Is Also Useful: Negative Correlation-Steered Latent Contrastive Learning

Heng Huang, Lei Luo, Jiexi Yan, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Fast Vehicle Identification in Surveillance via Ranked Semantic Sampling Based Embedding

Heng Huang, Feng Zheng, Xin Miao, 2018, IJCAI.

An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification

Bin Gu, Heng Huang, R. Bao, 2022, CIKM.

Towards Fairer Classifier via True Fairness Score Path

Bin Gu, Heng Huang, Xiang Li, 2022, CIKM.

Deep Relational Factorization Machines

Heng Huang, Gang Wu, Viswanathan Swaminathan, 2019 .

Supplementary Material of “Sparse Shrunk Additive Models”

Heng Huang, Hong Chen, Guodong Liu, 2020 .

Large Batch Optimization for Deep Learning Using New Complete Layer-Wise Adaptive Rate Scaling

Heng Huang, Zhouyuan Huo, Bin Gu, 2021, AAAI.

Large Batch Training Does Not Need Warmup pdf

Heng Huang, Zhouyuan Huo, Bin Gu, 2020, ArXiv.

An Iteratively Re-weighted Method for Problems with Sparsity-Inducing Norms pdf

Rong Wang, Feiping Nie, Heng Huang, 2019, ArXiv.

Fast OSCAR and OWL Regression via Safe Screening Rules

Bin Gu, Heng Huang, R. Bao, 2020, ICML.

Optimal Discrete Matrix Completion

Heng Huang, Ji Liu, Zhouyuan Huo, 2016, AAAI.

CommPOOL: An Interpretable Graph Pooling Framework for Hierarchical Graph Representation Learning pdf

Heng Huang, Guixiang Ma, Lifang He, 2020, Neural Networks.

Bilevel Distance Metric Learning for Robust Image Recognition

Jie Xu, Cheng Deng, Lei Luo, 2018, NeurIPS.

Deep Attributed Network Embedding

Heng Huang, Hongchang Gao, Heng Huang, 2018, IJCAI.

On the Random Conjugate Kernel and Neural Tangent Kernel

Heng Huang, Zhengmian Hu, Heng Huang, 2021, ICML.

Unsupervised Deep Generative Adversarial Hashing Network

Cheng Deng, Feng Zheng, Heng Huang, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Learning A Structured Optimal Bipartite Graph for Co-Clustering

Feiping Nie, Heng Huang, Cheng Deng, 2017, NIPS.

A Generalized Framework of Pathlength Associated Community Estimation for Brain Structural Network

Heng Huang, Alex D. Leow, Lei Guo, 2020, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

Conditional generative adversarial network for gene expression inference

Heng Huang, Xiaoqian Wang, Kamran Ghasedi Dizaji, 2018, Bioinform..

Robust Metric Learning on Grassmann Manifolds with Generalization Guarantees

Cheng Deng, Lei Luo, Jie Xu, 2019, AAAI.

New Graph-Blind Convolutional Network for Brain Connectome Data Analysis

Yanfu Zhang, Heng Huang, Heng Huang, 2019, IPMI.

Sinkhorn Regression

Jian Pei, Heng Huang, Lei Luo, 2020, IJCAI.

Multiclass Capped ℓp-Norm SVM for Robust Classifications

Feiping Nie, Heng Huang, Xiaoqian Wang, 2017, AAAI.

Safe Sample Screening for Robust Support Vector Machine

Xiang Li, Heng Huang, Bin Gu, 2019, AAAI.

Multi-Scale Fusion Subspace Clustering Using Similarity Constraint

Cheng Deng, Xu Yang, Heng Huang, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

FedDA: Faster Framework of Local Adaptive Gradient Methods via Restarted Dual Averaging

Heng Huang, Feihu Huang, Junyi Li, 2023, ArXiv.

On the Acceleration of Deep Learning Model Parallelism With Staleness

Zhouyuan Huo, Heng Huang, An Xu, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Binarized Neural Network for Single Image Super Resolution

Jie Li, Nannan Wang, Heng Huang, 2020, ECCV.

Nearest Neighbor Matching for Deep Clustering

Cheng Deng, Heng Huang, Zhiyuan Dang, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Multi-Horizon Time Series Forecasting with Temporal Attention Learning

Yi Pan, Di Wu, Jian Pei, 2019, KDD.

ProGAN: Network Embedding via Proximity Generative Adversarial Network

Jian Pei, Heng Huang, Hongchang Gao, 2019, KDD.

Deep Large-Scale Multi-task Learning Network for Gene Expression Inference

Wei Chen, Heng Huang, Kamran Ghasedi Dizaji, 2020, RECOMB.

Semi-Supervised Generative Adversarial Network for Gene Expression Inference

Heng Huang, Xiaoqian Wang, Kamran Ghasedi Dizaji, 2018, KDD.

Nesting-structured nuclear norm minimization for spatially correlated matrix variate

Jian Yang, Lei Luo, Yong Xu, 2019, Pattern Recognit..

Heterogeneous Memory Enhanced Multimodal Attention Model for Video Question Answering

Shu Zhang, Heng Huang, Chi Zhang, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Group Sparse Additive Machine

Hong Chen, Heng Huang, Cheng Deng, 2017, NIPS.

Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction

Heng Huang, Feihu Huang, Junyi Li, 2022, ArXiv.

Adaptive Serverless Learning pdf

Heng Huang, Hongchang Gao, Heng Huang, 2020, ArXiv.

Periodic Stochastic Gradient Descent with Momentum for Decentralized Training pdf

Heng Huang, Hongchang Gao, Heng Huang, 2020, ArXiv.

A Faster Decentralized Algorithm for Nonconvex Minimax Problems

Wenhan Xian, Feihu Huang, Heng Huang, 2021, NeurIPS.

Fast Training Method for Stochastic Compositional Optimization Problems

Heng Huang, Hongchang Gao, 2021, NeurIPS.

Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization

J. Pei, Heng Huang, Feihu Huang, 2020, J. Mach. Learn. Res..

Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems

Heng Huang, Feihu Huang, Xidong Wu, 2021, NeurIPS.

Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning pdf

Feihu Huang, Heng Huang, Junyi Li, 2021, ArXiv.

On the Convergence of Local Stochastic Compositional Gradient Descent with Momentum

Heng Huang, Hongchang Gao, Junyi Li, 2022, ICML.

AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization

Liefeng Bo, J. Pei, Bin Gu, 2021, KDD.

Privacy-Preserving Asynchronous Vertical Federated Learning Algorithms for Multiparty Collaborative Learning

Zhouyuan Huo, Bin Gu, Heng Huang, 2021, IEEE Transactions on Neural Networks and Learning Systems.

On the Convergence of Communication-Efficient Local SGD for Federated Learning

Heng Huang, Hongchang Gao, An Xu, 2021, AAAI.

Step-Ahead Error Feedback for Distributed Training with Compressed Gradient

Heng Huang, Zhouyuan Huo, An Xu, 2020, AAAI.

Double Momentum SGD for Federated Learning pdf

Heng Huang, An Xu, Heng Huang, 2021, ArXiv.

Learning Sampling Policy for Faster Derivative Free Optimization pdf

Heng Huang, Bin Gu, Zhou Zhai, 2021, ArXiv.

Zeroth-order Asynchronous Doubly Stochastic Algorithm with Variance Reduction pdf

Bin Gu, Heng Huang, Zhouyuan Huo, 2016, ArXiv.

Scalable Semi-Supervised SVM via Triply Stochastic Gradients

Bin Gu, Xiang Li, Wanli Shi, 2019, IJCAI.

Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization pdf

Heng Huang, Feihu Huang, Songcan Chen, 2019, IJCAI.

Network Pruning via Performance Maximization

Weidong Cai, Feihu Huang, Heng Huang, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse pdf

Heng Huang, Bin Gu, Junyi Li, 2021, AAAI.

BiAdam: Fast Adaptive Bilevel Optimization Methods pdf

Feihu Huang, Heng Huang, Heng Huang, 2021, ArXiv.

Disentangled Differentiable Network Pruning

Heng Huang, Feihu Huang, Yanfu Zhang, 2022, ECCV.

Recover Fair Deep Classification Models via Altering Pre-trained Structure

Heng Huang, Yanfu Zhang, Shangqian Gao, 2022, ECCV.

Exploration and Estimation for Model Compression

Heng Huang, Yanfu Zhang, Shangqian Gao, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Discrete Model Compression With Resource Constraint for Deep Neural Networks

Jian Pei, Feihu Huang, Shangqian Gao, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Unified Fairness from Data to Learning Algorithm

Heng Huang, Yanfu Zhang, Lei Luo, 2021, Industrial Conference on Data Mining.

Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating

Cheng Deng, Heng Huang, Bin Gu, 2021, AAAI.

Towards Transferable Targeted Attack

Cheng Deng, Junchi Yan, Heng Huang, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Wavelet-Based Dual Recursive Network for Image Super-Resolution

Jie Li, Nannan Wang, Heng Huang, 2020, IEEE Transactions on Neural Networks and Learning Systems.

Adaptive Hierarchical Similarity Metric Learning With Noisy Labels pdf

Cheng Deng, Heng Huang, Lei Luo, 2021, IEEE Transactions on Image Processing.

Learning Better Visual Data Similarities via New Grouplet Non-Euclidean Embedding

Heng Huang, Yanfu Zhang, Wenhan Xian, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Unsupervised Hyperbolic Metric Learning

Heng Huang, Lei Luo, Jiexi Yan, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Improved Bilevel Model: Fast and Optimal Algorithm with Theoretical Guarantee pdf

Heng Huang, Junyi Li, Bin Gu, 2020, ArXiv.

Conditional Random Field Enhanced Graph Convolutional Neural Networks

Jian Pei, Heng Huang, Hongchang Gao, 2019, KDD.

A Unified q-Memorization Framework for Asynchronous Stochastic Optimization

Heng Huang, Zhouyuan Huo, Wenhan Xian, 2020, J. Mach. Learn. Res..

Faster On-Device Training Using New Federated Momentum Algorithm pdf

Lawrence Carin, Qian Yang, Heng Huang, 2020, ArXiv.

Faster Secure Data Mining via Distributed Homomorphic Encryption

Heng Huang, Junyi Li, Heng Huang, 2020, KDD.

Disentangled and Proportional Representation Learning for Multi-view Brain Connectomes

Shandong Wu, Heng Huang, Liang Zhan, 2021, MICCAI.

Integrating Heterogeneous Brain Networks for Predicting Brain Disease Conditions

Paul Thompson, Weidong Cai, Liang Zhan, 2019, MICCAI.

Ouroboros: On Accelerating Training of Transformer-Based Language Models

Lawrence Carin, Qian Yang, Heng Huang, 2019, NeurIPS.

Accelerated Zeroth-Order Momentum Methods from Mini to Minimax Optimization

J. Pei, Heng Huang, Feihu Huang, 2020, arXiv.org.

Balanced Self-Paced Learning for Generative Adversarial Clustering Network

Cheng Deng, Heng Huang, Xiaoqian Wang, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Tackle Balancing Constraint for Incremental Semi-Supervised Support Vector Learning

Jian Pei, Bin Gu, Heng Huang, 2019, KDD.

New Incremental Learning Algorithm for Semi-Supervised Support Vector Machine

Bin Gu, Heng Huang, Xiao-Tong Yuan, 2018, KDD.

Stochastic Second-Order Method for Large-Scale Nonconvex Sparse Learning Models

Heng Huang, Hongchang Gao, Heng Huang, 2018, IJCAI.

Brain Dynamics Through the Lens of Statistical Mechanics by Unifying Structure and Function

Lei Guo, Alex D. Leow, Dan Schonfeld, 2019, MICCAI.

Optimal Underdamped Langevin MCMC Method

Heng Huang, Feihu Huang, Zhengmian Hu, 2021, NeurIPS.

Local Centroids Structured Non-Negative Matrix Factorization

Feiping Nie, Heng Huang, Hongchang Gao, 2017, AAAI.

Cross Domain Model Compression by Structurally Weight Sharing

Cheng Deng, Heng Huang, Shangqian Gao, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Direct Shape Regression Networks for End-to-End Face Alignment

Heng Huang, Xiantong Zhen, Xianglong Liu, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Asynchronous Stochastic Frank-Wolfe Algorithms for Non-Convex Optimization

Heng Huang, Bin Gu, Wenhan Xian, 2019, IJCAI.

Multi-Level Metric Learning via Smoothed Wasserstein Distance

Heng Huang, Jie Xu, Cheng Deng, 2018, IJCAI.

Biological Knowledge Guided Deep Neural Network for Brain Genotype-Phenotype Association Study

Paul M. Thompson, Liang Zhan, Heng Huang, 2019, MBIA/MFCA@MICCAI.

Cognitive Assessment Prediction in Alzheimer’s Disease by Multi-Layer Multi-Target Regression

Quanzheng Li, D. Shen, Heng Huang, 2018, Neuroinformatics.

Regularized Modal Regression with Applications in Cognitive Impairment Prediction

Dinggang Shen, Hong Chen, Heng Huang, 2017, NIPS.

Momentum-Based Policy Gradient Methods pdf

Feihu Huang, Shangqian Gao, Jian Pei, 2020, ICML.

Can Stochastic Zeroth-Order Frank-Wolfe Method Converge Faster for Non-Convex Problems?

Heng Huang, Hongchang Gao, Heng Huang, 2020, ICML.

Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines

Bin Gu, Heng Huang, Cheng Deng, 2018, ICML.

A Bayesian Federated Learning Framework with Online Laplace Approximation

Ling Shao, Guo-Jun Qi, Heng Huang, 2021, 2102.01936.

Drosophila Gene Expression Pattern Annotations via Multi-Instance Biological Relevance Learning

Hua Wang, Heng Huang, Xinbo Gao, 2016, AAAI.

Bregman Gradient Policy Optimization

Heng Huang, Feihu Huang, Shangqian Gao, 2021, ICLR.

Communication-Efficient Adam-Type Algorithms for Distributed Data Mining

Heng Huang, Feihu Huang, Wenhan Xian, 2022, Industrial Conference on Data Mining.

AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization

Heng Huang, Feihu Huang, 2021, AISTATS.

Inexact Proximal Gradient Methods for Non-convex and Non-smooth Optimization pdf

Heng Huang, Zhouyuan Huo, Bin Gu, 2016, AAAI.

Training Faster with Compressed Gradient pdf

Heng Huang, Zhouyuan Huo, An Xu, 2020, ArXiv.

Communication-Efficient Frank-Wolfe Algorithm for Nonconvex Decentralized Distributed Learning

Feihu Huang, Heng Huang, Wenhan Xian, 2021, AAAI.

Efficient Approximate Solution Path Algorithm for Order Weight L_1-Norm with Accuracy Guarantee

Heng Huang, Bin Gu, Runxue Bao, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

Fast Stochastic Recursive Momentum Methods for Imbalanced Data Mining

Heng Huang, Feihu Huang, Xidong Wu, 2022, 2022 IEEE International Conference on Data Mining (ICDM).

Asynchronous Mini-Batch Gradient Descent with Variance Reduction for Non-Convex Optimization

Heng Huang, Zhouyuan Huo, Zhouyuan Huo, 2017, AAAI.

Sparse Shrunk Additive Models

Heng Huang, Hong Chen, Guodong Liu, 2020, ICML.

Scaling Up Generalized Kernel Methods

Zhouyuan Huo, Bin Gu, Heng Huang, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Scalable Kernel Ordinal Regression via Doubly Stochastic Gradients

Xiang Li, Cheng Deng, Xiang Geng, 2020, IEEE Transactions on Neural Networks and Learning Systems.

Accelerated Method for Stochastic Composition Optimization with Nonsmooth Regularization

Heng Huang, Zhouyuan Huo, Bin Gu, 2017, AAAI.

Approaching Machine Learning Fairness through Adversarial Network pdf

Heng Huang, Xiaoqian Wang, Heng Huang, 2019, ArXiv.

New Balanced Active Learning Model and Optimization Algorithm

Heng Huang, Yijun Huang, Ji Liu, 2018, IJCAI.

Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization

Heng Huang, Feihu Huang, Songcan Chen, 2020, ICML.

Iteratively Re-Weighted Method for Sparsity-Inducing Norms

F. Nie, Heng Huang, Xiaoqian Wang, 2023, IEEE Transactions on Knowledge and Data Engineering.

Adversarial Nonnegative Matrix Factorization

Lei Luo, Heng Huang, Yanfu Zhang, 2020, ICML.

Joint Generative Moment-Matching Network for Learning Structural Latent Code

Heng Huang, Hongchang Gao, Heng Huang, 2018, IJCAI.

Training Neural Networks Using Features Replay

Bin Gu, Heng Huang, Zhouyuan Huo, 2018, NeurIPS.

Inexact Proximal Gradient Methods for Non-convex and Non-smooth Optimization

Zhouyuan Huo, Bin Gu, Heng Huang, 2016, AAAI.

Sinkhorn Regression

J. Pei, Heng Huang, Lei Luo, 2020, IJCAI.

Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization

Bin Gu, Heng Huang, Xiang Li, 2019, IJCAI.

Triply stochastic gradient method for large-scale nonlinear similar unlabeled classification

Cheng Deng, Heng Huang, Bin Gu, 2021, Machine Learning.

Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization

Heng Huang, Wanli Shi, Bin Gu, 2019, AAAI.

Asynchronous Doubly Stochastic Group Regularized Learning

Bin Gu, Heng Huang, Zhouyuan Huo, 2018, AISTATS.

Brain Connectome Based Complex Brain Disorder Prediction via Novel Graph-Blind Convolutional Network

Heng Huang, Yanfu Zhang, 2019 .

A new large-scale learning algorithm for generalized additive models

Zhouyuan Huo, Bin Gu, Heng Huang, 2023, Machine-mediated learning.

Desirable Companion for Vertical Federated Learning: New Zeroth-Order Gradient Based Algorithm

Cheng Deng, Heng Huang, Bin Gu, 2021, CIKM.

Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm pdf

Xiang Geng, Heng Huang, Bin Gu, 2021, ArXiv.

Orthogonality-Promoting Dictionary Learning via Bayesian Inference

Cheng Deng, Lei Luo, Jie Xu, 2019, AAAI.

New Robust Metric Learning Model Using Maximum Correntropy Criterion

Jie Xu, Heng Huang, Cheng Deng, 2018, KDD.

Decoupled Asynchronous Proximal Stochastic Gradient Descent with Variance Reduction pdf

Bin Gu, Heng Huang, Zhouyuan Huo, 2016, ArXiv.

Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning pdf

Cheng Deng, Heng Huang, Zhouyuan Huo, 2020, ArXiv.

Nonconvex Zeroth-Order Stochastic ADMM Methods with Lower Function Query Complexity pdf

Jian Pei, Feihu Huang, Heng Huang, 2019, ArXiv.

Interpretations Steered Network Pruning via Amortized Inferred Saliency Maps

Heng Huang, Shangqian Gao, Alireza Ganjdanesh, 2022, ECCV.

New Robust Clustering Model for Identifying Cancer Genome Landscapes

Heng Huang, Xiaoqian Wang, Hongchang Gao, 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning

Heng Huang, Feihu Huang, Junyi Li, 2021, ArXiv.

Black-Box Reductions for Zeroth-Order Gradient Algorithms to Achieve Lower Query Complexity

Bin Gu, Heng Huang, Shangqian Gao, 2021, J. Mach. Learn. Res..

Improving Social Network Embedding via New Second-Order Continuous Graph Neural Networks

Heng Huang, Yanfu Zhang, Shangqian Gao, 2022, KDD.

Video Recovery via Learning Variation and Consistency of Images

Heng Huang, Weidong Cai, Shangqian Gao, 2017, AAAI.

Doubly Contrastive Deep Clustering pdf

Cheng Deng, Heng Huang, Zhiyuan Dang, 2021, ArXiv.

Curvilinear Distance Metric Learning

Chen Gong, Jun Li, Lei Luo, 2019, NeurIPS.