Haohan Wang

According to our database, Haohan Wang authored at least 94 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

SAR Incremental Automatic Target Recognition Based on Mutual Information Maximization.

Bin Li, Zongyong Cui, Haohan Wang, Yijie Deng, Jizhen Ma, Jianyu Yang, Zongjie Cao

IEEE Geosci. Remote. Sens. Lett., 2024

Approximate Nullspace Augmented Finetuning for Robust Vision Transformers.

Haoyang Liu, Aditya Singh, Yijiang Li, Haohan Wang

CoRR, 2024

Towards Adversarially Robust Dataset Distillation by Curvature Regularization.

Eric Xue, Yijiang Li, Haoyang Liu, Yifan Shen, Haohan Wang

CoRR, 2024

Beyond Finite Data: Towards Data-free Out-of-distribution Generalization via Extrapolation.

Yijiang Li, Sucheng Ren, Weipeng Deng, Yuzhi Xu, Ying Gao, Edith C. H. Ngai, Haohan Wang

CoRR, 2024

Toward a Team of AI-made Scientists for Scientific Discovery from Gene Expression Data.

Haoyang Liu, Yijiang Li, Jinglin Jian, Yuxuan Cheng, Jianrong Lu, Shuyi Guo, Jinglei Zhu, Mianchen Zhang, Miantong Zhang, Haohan Wang

CoRR, 2024

GUARD: Role-playing to Generate Natural-language Jailbreakings to Test Guideline Adherence of Large Language Models.

Haibo Jin, Ruoxi Chen, Andy Zhou, Jinyin Chen, Yang Zhang, Haohan Wang

CoRR, 2024

Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks.

Andy Zhou, Bo Li, Haohan Wang

CoRR, 2024

MedTransformer: Accurate AD Diagnosis for 3D MRI Images through 2D Vision Transformers.

Yifeng Wang, Ke Chen, Yihan Zhang, Haohan Wang

CoRR, 2024

2023

Efficient Few-Shot Classification via Contrastive Pretraining on Web Data.

Zhuoling Li, Haohan Wang, Tymoteusz Swistek, En Yu, Haoqian Wang

IEEE Trans. Artif. Intell., June, 2023

Generate E-commerce Product Background by Integrating Category Commonality and Personalized Style.

Haohan Wang, Wei Feng, Yang Lu, Yaoyu Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junjie Shen, Zhangang Lin, Lixing Bo, Jingping Shao

CoRR, 2023

Dataset Distillation via the Wasserstein Metric.

Haoyang Liu, Tiancheng Xing, Luwei Li, Vibhu Dalal, Jingrui He, Haohan Wang

CoRR, 2023

Beyond Pixels: Exploring Human-Readable SVG Generation for Simple Images with Vision Language Models.

Tong Zhang, Haoyang Liu, Peiyan Zhang, Yuxuan Cheng, Haohan Wang

CoRR, 2023

Choosing Wisely and Learning Deeply: Selective Cross-Modality Distillation via CLIP for Domain Generalization.

Jixuan Leng, Yijiang Li, Haohan Wang

CoRR, 2023

ZooPFL: Exploring Black-box Foundation Models for Personalized Federated Learning.

Wang Lu, Hao Yu, Jindong Wang, Damien Teney, Haohan Wang, Yiqiang Chen, Qiang Yang, Xing Xie, Xiangyang Ji

CoRR, 2023

Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models.

Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, Yu-Xiong Wang

CoRR, 2023

Understanding Adversarial Transferability in Federated Learning.

Yijiang Li, Ying Gao, Haohan Wang

CoRR, 2023

Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models.

Peiyan Zhang, Haoyang Liu, Chaozhuo Li, Xing Xie, Sunghun Kim, Haohan Wang

CoRR, 2023

Towards Trustworthy and Aligned Machine Learning: A Data-centric Survey with Causality Perspectives.

Haoyang Liu, Maheep Chaudhary, Haohan Wang

CoRR, 2023

Leveraging Large Language Models for Scalable Vector Graphics-Driven Image Understanding.

Mu Cai, Zeyi Huang, Yuheng Li, Haohan Wang, Yong Jae Lee

CoRR, 2023

BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise Learning.

Jingfeng Zhang, Bo Song, Haohan Wang, Bo Han, Tongliang Liu, Lei Liu, Masashi Sugiyama

CoRR, 2023

Iterative Few-shot Semantic Segmentation from Image Label Text.

Haohan Wang, Liang Liu, Wuhao Zhang, Jiangning Zhang, Zhenye Gan, Yabiao Wang, Chengjie Wang, Haoqian Wang

CoRR, 2023

Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network.

Peiyan Zhang, Jiayan Guo, Chaozhuo Li, Yueqi Xie, Jaeboum Kim, Yan Zhang, Xing Xie, Haohan Wang, Sunghun Kim

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models.

Andy Zhou, Jindong Wang, Yu-Xiong Wang, Haohan Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adaptive Test-Time Personalization for Federated Learning.

Wenxuan Bao, Tianxin Wei, Haohan Wang, Jingrui He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Trustworthy Machine Learning: Robustness, Generalization, and Interpretability.

Jindong Wang, Haoliang Li, Haohan Wang, Sinno Jialin Pan, Xing Xie

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Optimizing the Collaboration Structure in Cross-Silo Federated Learning.

Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He

Proceedings of the International Conference on Machine Learning, 2023

Trustworthy Computing for Biomedical Challenges.

Haohan Wang

Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

A Sentence Speaks a Thousand Images: Domain Generalization through Distilling CLIP with Language Guidance.

Zeyi Huang, Andy Zhou, Zijian Lin, Mu Cai, Haohan Wang, Yong Jae Lee

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Self-learning for Annotating Website Privacy Policies at Scale.

Shufan Ming, Haohan Wang

Proceedings of the 47th IEEE Annual Computers, Software, and Applications Conference, 2023

Toward Robust Diagnosis: A Contour Attention Preserving Adversarial Defense for COVID-19 Detection.

Kun Xiang, Xing Zhang, Jinwen She, Jinpeng Liu, Haohan Wang, Shiqi Deng, Shancheng Jiang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Calibrated Teacher for Sparsely Annotated Object Detection.

Haohan Wang, Liang Liu, Boshen Zhang, Jiangning Zhang, Wuhao Zhang, Zhenye Gan, Yabiao Wang, Chengjie Wang, Haoqian Wang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Few-Shot Steel Surface Defect Detection.

Haohan Wang, Zhuoling Li, Haoqian Wang

IEEE Trans. Instrum. Meas., 2022

Kernel Mixed Model for Transcriptome Association Study.

Haohan Wang, Oscar Lopez, Eric P. Xing, Wei Wu

J. Comput. Biol., 2022

Trade-offs of Linear Mixed Models in Genome-Wide Association Studies.

Haohan Wang, Bryon Aragam, Eric P. Xing

J. Comput. Biol., 2022

Expeditious Saliency-guided Mix-up through Random Gradient Thresholding.

Minh-Long Luu, Zeyi Huang, Eric P. Xing, Yong Jae Lee, Haohan Wang

CoRR, 2022

A Principled Evaluation Protocol for Comparative Investigation of the Effectiveness of DNN Classification Models on Similar-but-non-identical Datasets.

Esla Timothy Anzaku, Haohan Wang, Arnout Van Messem, Wesley De Neve

CoRR, 2022

Robustar: Interactive Toolbox Supporting Precise Data Annotation for Robust Vision Learning.

Chonghan Chen, Haohan Wang, Leyang Hu, Yuhao Zhang, Shuguang Lyu, Jingcheng Wu, Xinnuo Li, Linjing Sun, Eric P. Xing

CoRR, 2022

MRCLens: an MRC Dataset Bias Detection Toolkit.

Yifan Zhong, Haohan Wang, Eric P. Xing

CoRR, 2022

Bear the Query in Mind: Visual Grounding with Query-conditioned Convolution.

Chonghan Chen, Qi Jiang, Chih-Hao Wang, Noel Chen, Haohan Wang, Xiang Li, Bhiksha Raj

CoRR, 2022

The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain Generalization.

Zeyi Huang, Haohan Wang, Dong Huang, Yong Jae Lee, Eric P. Xing

CoRR, 2022

Toward learning human-aligned cross-domain robust models by countering misaligned features.

Haohan Wang, Zeyi Huang, Hanlin Zhang, Yong Jae Lee, Eric P. Xing

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Gene Set Priorization Guided by Regulatory Networks with p-values through Kernel Mixed Model.

Haohan Wang, Oscar L. Lopez, Wei Wu, Eric P. Xing

Proceedings of the Research in Computational Molecular Biology, 2022

Measure and Improve Robustness in NLP Models: A Survey.

Xuezhi Wang, Haohan Wang, Diyi Yang

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation.

Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Iterative Few-shot Semantic Segmentation from Image Label Text.

Haohan Wang, Liang Liu, Wuhao Zhang, Jiangning Zhang, Zhenye Gan, Yabiao Wang, Chengjie Wang, Haoqian Wang

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

The Two Dimensions of Worst-case Training and Their Integrated Effect for Out-of-domain Generalization.

Zeyi Huang, Haohan Wang, Dong Huang, Yong Jae Lee, Eric P. Xing

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Toward Learning Human-aligned Cross-domain Robust Models by Countering Misaligned Features.

Haohan Wang, Zeyi Huang, Hanlin Zhang, Eric Poe Xing

CoRR, 2021

Tradeoffs of Linear Mixed Models in Genome-wide Association Studies.

Haohan Wang, Bryon Aragam, Eric P. Xing

CoRR, 2021

Enabling the Network to Surf the Internet.

Zhuoling Li, Haohan Wang, Tymoteusz Swistek, Weixin Chen, Yuanzheng Li, Haoqian Wang

CoRR, 2021

Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets.

Haohan Wang, Fen Pei, Michael M. Vanyukov, Ivet Bahar, Wei Wu, Eric P. Xing

BMC Bioinform., 2021

Active learning to classify macromolecular structures in situ for less supervision in cryo-electron tomography.

Xuefeng Du, Haohan Wang, Zhenxi Zhu, Xiangrui Zeng, Yi-Wei Chang, Jing Zhang, Eric P. Xing, Min Xu

Bioinform., 2021

Robust Contrastive Learning Using Negative Samples with Diminished Semantics.

Songwei Ge, Shlok Mishra, Chun-Liang Li, Haohan Wang, David Jacobs

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Poly(A)-DG: A deep-learning-based domain generalization method to identify cross-species Poly(A) signal without prior knowledge from target species.

Yumin Zheng, Haohan Wang, Yang Zhang, Xin Gao, Eric P. Xing, Min Xu

PLoS Comput. Biol., November, 2020

Squared 𝓁₂ Norm as Consistency Loss for Leveraging Augmented Data to Learn Robust and Invariant Representations.

Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing

CoRR, 2020

Word Shape Matters: Robust Machine Translation with Visual Embedding.

Haohan Wang, Peiyan Zhang, Eric P. Xing

CoRR, 2020

Supervised Adversarial Alignment of Single-Cell RNA-seq Data.

Songwei Ge, Haohan Wang, Amir Alavi, Eric P. Xing, Ziv Bar-Joseph

Proceedings of the Research in Computational Molecular Biology, 2020

Self-challenging Improves Cross-Domain Generalization.

Zeyi Huang, Haohan Wang, Eric P. Xing, Dong Huang

Proceedings of the Computer Vision - ECCV 2020, 2020

High-Frequency Component Helps Explain the Generalization of Convolutional Neural Networks.

Haohan Wang, Xindi Wu, Zeyi Huang, Eric P. Xing

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Anomaly Detection in Road Networks Using Sliding-Window Tensor Factorization.

Ming Xu, Jianping Wu, Haohan Wang, Mengxin Cao

IEEE Trans. Intell. Transp. Syst., 2019

Discovery of Critical Nodes in Road Networks Through Mining From Vehicle Trajectories.

Ming Xu, Jianping Wu, Mengqi Liu, Yunpeng Xiao, Haohan Wang, Dongmei Hu

IEEE Trans. Intell. Transp. Syst., 2019

High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks.

Haohan Wang, Xindi Wu, Pengcheng Yin, Eric P. Xing

CoRR, 2019

Deep mixed model for marginal epistasis detection and population stratification correction in genome-wide association studies.

Haohan Wang, Tianwei Yue, Jingkang Yang, Wei Wu, Eric P. Xing

BMC Bioinform., 2019

Precision Lasso: accounting for correlations and linear dependencies in high-dimensional genomic data.

Haohan Wang, Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing

Bioinform., 2019

Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications.

Haohan Wang, Zhenglin Wu, Eric P. Xing

Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019

Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning.

Haohan Wang, Xiang Liu, Yifeng Tao, Wenting Ye, Qiao Jin, William W. Cohen, Eric P. Xing

Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019

Learning Robust Global Representations by Penalizing Local Predictive Power.

Haohan Wang, Songwei Ge, Zachary C. Lipton, Eric P. Xing

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning Robust Representations by Projecting Superficial Statistics Out.

Haohan Wang, Zexue He, Zachary C. Lipton, Eric P. Xing

Proceedings of the 7th International Conference on Learning Representations, 2019

Regularized Adversarial Training (RAT) for Robust Cellular Electron Cryo Tomograms Classification.

Xindi Wu, Yijun Mao, Haohan Wang, Xiangrui Zeng, Xin Gao, Eric P. Xing, Min Xu

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Deep Inductive Matrix Completion for Biomedical Interaction Prediction.

Haohan Wang, Yibing Wei, Mengxin Cao, Ming Xu, Wei Wu, Eric P. Xing

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Graph-structured Sparse Mixed Models for Genetic Association with Confounding Factors Correction.

Haohan Wang, Changpeng Lu, Wei Wu, Eric P. Xing

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual.

He He, Sheng Zha, Haohan Wang

Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP, 2019

What if We Simply Swap the Two Text Fragments? A Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks.

Haohan Wang, Da Sun, Eric P. Xing

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

3-HBP: A Three-Level Hidden Bayesian Link Prediction Model in Social Networks.

Yunpeng Xiao, Xixi Li, Haohan Wang, Ming Xu, Yanbing Liu

IEEE Trans. Comput. Soc. Syst., 2018

Fair Deep Learning Prediction for Healthcare Applications with Confounder Filtering.

Zhenglin Wu, Haohan Wang, Mingze Cao, Yin Chen, Eric P. Xing

CoRR, 2018

Deep Learning for Genomics: A Concise Overview.

Tianwei Yue, Haohan Wang

CoRR, 2018

GLDA-FP: Gaussian LDA Model for Forward Prediction.

Yunpeng Xiao, Liangyun Liu, Ming Xu, Haohan Wang, Yanbing Liu

Proceedings of the Big Data - BigData 2018, 2018

Heterogeneous Hi-C Data Super-resolution with a Conditional Generative Adversarial Network.

Yifeng Chen, Wei Sun, Haohan Wang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

2017

Extracting compact representation of knowledge from gene expression data for protein-protein interaction.

Haohan Wang, Aman Gupta, Ming Xu

Int. J. Data Min. Bioinform., 2017

A Sparse Graph-Structured Lasso Mixed Model for Genetic Association with Confounding Correction.

Wenting Ye, Xiang Liu, Haohan Wang, Eric P. Xing

CoRR, 2017

On the Origin of Deep Learning.

Haohan Wang, Bhiksha Raj, Eric P. Xing

CoRR, 2017

Select-additive learning: Improving generalization in multimodal sentiment analysis.

Haohan Wang, Aaksha Meghawat, Louis-Philippe Morency, Eric P. Xing

Proceedings of the 2017 IEEE International Conference on Multimedia and Expo, 2017

Multiplex confounding factor correction for genomic association mapping with squared sparse linear mixed model.

Haohan Wang, Xiang Liu, Yunpeng Xiao, Ming Xu, Eric P. Xing

Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

Variable selection in heterogeneous datasets: A truncated-rank sparse linear mixed model with applications to genome-wide association studies.

Haohan Wang, Bryon Aragam, Eric P. Xing

Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

2016

SeDMiD for Confusion Detection: Uncovering Mind State from Time Series Brain Wave Data.

Jingkang Yang, Haohan Wang, Jun Zhu, Eric P. Xing

CoRR, 2016

Select-Additive Learning: Improving Cross-individual Generalization in Multimodal Sentiment Analysis.

Haohan Wang, Aaksha Meghawat, Louis-Philippe Morency, Eric P. Xing

CoRR, 2016

Multiple confounders correction with regularized linear mixed effect models, with application in biological processes.

Haohan Wang, Jingkang Yang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

2015

A Survey: Time Travel in Deep Learning Space: An Introduction to Deep Learning Models and How Deep Learning Models Evolved from the Initial Ideas.

Haohan Wang, Bhiksha Raj

CoRR, 2015

Evaluating Protein-protein Interaction Predictors with a Novel 3-Dimensional Metric.

Haohan Wang, Madhavi K. Ganapathiraju

CoRR, 2015

Evaluation of Protein-protein Interaction Predictors with Noisy Partially Labeled Data Sets.

Haohan Wang, Madhavi K. Ganapathiraju

CoRR, 2015

Learning structure in gene expression data using deep architectures, with an application to gene clustering.

Aman Gupta, Haohan Wang, Madhavi K. Ganapathiraju

Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015

2014

Discovery of Important Crossroads in Road Network using Massive Taxi Trajectories.

Ming Xu, Jianping Wu, Yiman Du, Haohan Wang, Geqi Qi, Kezhen Hu, Yunpeng Xiao

CoRR, 2014

Multimodal Transfer Deep Learning for Audio Visual Recognition.

Seungwhan Moon, Suyoun Kim, Haohan Wang

CoRR, 2014

2013

Behavior analysis of low-literate users of a viral speech-based telephone service.

Haohan Wang, Agha Ali Raza, Yibin Lin, Roni Rosenfeld

Proceedings of the Annual Symposium on Computing for Development, 2013

Using EEG to Improve Massive Open Online Courses Feedback Interaction.

Haohan Wang, Yiwei Li, Xiaobo Hu, Yucong Yang, Zhu Meng, Kai-Min Chang

Proceedings of the Workshops at the 16th International Conference on Artificial Intelligence in Education AIED 2013, 2013