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2020 – today
- 2024
[j17]Bin Li
, Zongyong Cui, Haohan Wang, Yijie Deng, Jizhen Ma, Jianyu Yang, Zongjie Cao:
SAR Incremental Automatic Target Recognition Based on Mutual Information Maximization. IEEE Geosci. Remote. Sens. Lett. 21: 1-5 (2024)- [j16]Jingfeng Zhang, Bo Song, Haohan Wang, Bo Han, Tongliang Liu, Lei Liu, Masashi Sugiyama:
BadLabel: A Robust Perspective on Evaluating and Enhancing Label-Noise Learning. IEEE Trans. Pattern Anal. Mach. Intell. 46(6): 4398-4409 (2024) - [j15]Jixuan Leng, Yijiang Li, Haohan Wang:
Choosing Wisely and Learning Deeply: Selective Cross-Modality Distillation via CLIP for Domain Generalization. Trans. Mach. Learn. Res. 2024 (2024) - [c50]Huaming Chen, Jun Zhuang, Yu Yao, Wei Jin, Haohan Wang, Yong Xie, Chi-Hung Chi, Kim-Kwang Raymond Choo:
Trustworthy and Responsible AI for Information and Knowledge Management System. CIKM 2024: 5574-5576 - [c49]Haibo Jin, Ruoxi Chen, Jinyin Chen, Haibin Zheng, Yang Zhang, Haohan Wang:
CatchBackdoor: Backdoor Detection via Critical Trojan Neural Path Fuzzing. ECCV (47) 2024: 90-106 - [c48]Ruoxi Chen, Haibo Jin, Yixin Liu, Jinyin Chen, Haohan Wang, Lichao Sun:
EditShield: Protecting Unauthorized Image Editing by Instruction-Guided Diffusion Models. ECCV (63) 2024: 126-142 - [c47]Aditya Singh, Haohan Wang:
Simple Unsupervised Knowledge Distillation With Space Similarity. ECCV (2) 2024: 147-164 - [c46]Zhenbang Du, Wei Feng, Haohan Wang, Yaoyu Li, Jingsen Wang, Jian Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junsheng Jin, Junjie Shen, Zhangang Lin, Jingping Shao:
Towards Reliable Advertising Image Generation Using Human Feedback. ECCV (20) 2024: 399-415 - [c45]Siddhant Bikram Shah, Shuvam Shiwakoti, Maheep Chaudhary, Haohan Wang:
MemeCLIP: Leveraging CLIP Representations for Multimodal Meme Classification. EMNLP 2024: 17320-17332 - [c44]Xinyan Zhang, Haohan Wang:
User Preferences for Icon Design Styles and Their Associations with Personality and Demographic. HCI (56) 2024: 235-245 - [c43]Lei Chu, Haohan Wang, Andreas F. Molisch:
Model-Agnostic Channel Prediction with Meta Predictive Recurrent Neural Networks. ICC Workshops 2024: 1962-1967 - [c42]Peiyan Zhang, Haoyang Liu, Chaozhuo Li, Xing Xie, Sunghun Kim, Haohan Wang:
Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models. ICLR 2024 - [c41]Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, Yu-Xiong Wang:
Language Agent Tree Search Unifies Reasoning, Acting, and Planning in Language Models. ICML 2024 - [c40]Haohan Wang, Zongyong Cui, Chang Lu, Zongjie Cao:
A Lightweight Network for Radar Specific Emitter Identification via Differential Constellation Figure. IGARSS 2024: 9096-9099 - [c39]Wei Jin, Haohan Wang, Daochen Zha, Qiaoyu Tan, Yao Ma, Sharon Li, Su-In Lee:
DCAI: Data-centric Artificial Intelligence. WWW (Companion Volume) 2024: 1482-1485 - [i72]Yifeng Wang, Ke Chen, Yihan Zhang, Haohan Wang:
MedTransformer: Accurate AD Diagnosis for 3D MRI Images through 2D Vision Transformers. CoRR abs/2401.06349 (2024) - [i71]Andy Zhou, Bo Li, Haohan Wang:
Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks. CoRR abs/2401.17263 (2024) - [i70]Haibo Jin, Ruoxi Chen, Andy Zhou, Jinyin Chen, Yang Zhang, Haohan Wang:
GUARD: Role-playing to Generate Natural-language Jailbreakings to Test Guideline Adherence of Large Language Models. CoRR abs/2402.03299 (2024) - [i69]Haoyang Liu, Yijiang Li, Jinglin Jian, Yuxuan Cheng, Jianrong Lu, Shuyi Guo, Jinglei Zhu, Mianchen Zhang, Miantong Zhang, Haohan Wang:
Toward a Team of AI-made Scientists for Scientific Discovery from Gene Expression Data. CoRR abs/2402.12391 (2024) - [i68]Yijiang Li, Sucheng Ren, Weipeng Deng, Yuzhi Xu, Ying Gao, Edith C. H. Ngai, Haohan Wang:
Beyond Finite Data: Towards Data-free Out-of-distribution Generalization via Extrapolation. CoRR abs/2403.05523 (2024) - [i67]Eric Xue, Yijiang Li, Haoyang Liu, Yifan Shen, Haohan Wang:
Towards Adversarially Robust Dataset Distillation by Curvature Regularization. CoRR abs/2403.10045 (2024) - [i66]Haoyang Liu, Aditya Singh, Yijiang Li, Haohan Wang:
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers. CoRR abs/2403.10476 (2024) - [i65]Pengzhi Li, Yikang Ding, Haohan Wang, Chengshuai Tang, Zhiheng Li:
The Devil is in the Edges: Monocular Depth Estimation with Edge-aware Consistency Fusion. CoRR abs/2404.00373 (2024) - [i64]Haibo Jin, Andy Zhou, Joe D. Menke, Haohan Wang:
Jailbreaking Large Language Models Against Moderation Guardrails via Cipher Characters. CoRR abs/2405.20413 (2024) - [i63]Yifeng Wang, Weipeng Li, Thomas Pearce, Haohan Wang:
From Tissue Plane to Organ World: A Benchmark Dataset for Multimodal Biomedical Image Registration using Deep Co-Attention Networks. CoRR abs/2406.04105 (2024) - [i62]Chengyuan Deng, Yiqun Duan, Xin Jin, Heng Chang, Yijun Tian, Han Liu, Henry Peng Zou, Yiqiao Jin, Yijia Xiao, Yichen Wang, Shenghao Wu, Zongxing Xie, Kuofeng Gao, Sihong He, Jun Zhuang, Lu Cheng, Haohan Wang:
Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas. CoRR abs/2406.05392 (2024) - [i61]Haoyang Liu, Haohan Wang:
GenoTEX: A Benchmark for Evaluating LLM-Based Exploration of Gene Expression Data in Alignment with Bioinformaticians. CoRR abs/2406.15341 (2024) - [i60]Haibo Jin, Leyang Hu, Xinuo Li, Peiyan Zhang, Chonghan Chen, Jun Zhuang, Haohan Wang:
JailbreakZoo: Survey, Landscapes, and Horizons in Jailbreaking Large Language and Vision-Language Models. CoRR abs/2407.01599 (2024) - [i59]Yihan Zhang, Xuanshuo Zhang, Wei Wu, Haohan Wang:
Quantitative Evaluation of the Saliency Map for Alzheimer's Disease Classifier with Anatomical Segmentation. CoRR abs/2407.08546 (2024) - [i58]Zhenbang Du, Wei Feng, Haohan Wang, Yaoyu Li, Jingsen Wang, Jian Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junsheng Jin, Junjie Shen, Zhangang Lin, Jingping Shao:
Towards Reliable Advertising Image Generation Using Human Feedback. CoRR abs/2408.00418 (2024) - [i57]Thomas Yu Chow Tam, Litian Liang, Ke Chen, Haohan Wang, Wei Wu:
A Quantitative Approach for Evaluating Disease Focus and Interpretability of Deep Learning Models for Alzheimer's Disease Classification. CoRR abs/2409.04888 (2024) - [i56]Ke Chen, Yifeng Wang, Yufei Zhou, Haohan Wang:
DS-ViT: Dual-Stream Vision Transformer for Cross-Task Distillation in Alzheimer's Early Diagnosis. CoRR abs/2409.07584 (2024) - [i55]Aditya Singh, Haohan Wang:
Simple Unsupervised Knowledge Distillation With Space Similarity. CoRR abs/2409.13939 (2024) - [i54]Siddhant Bikram Shah, Shuvam Shiwakoti, Maheep Chaudhary, Haohan Wang:
MemeCLIP: Leveraging CLIP Representations for Multimodal Meme Classification. CoRR abs/2409.14703 (2024) - [i53]Peiran Wang, Haohan Wang:
DistDD: Distributed Data Distillation Aggregation through Gradient Matching. CoRR abs/2410.08665 (2024) - [i52]Zhiyu Xue, Haohan Wang, Yao Qin, Ramtin Pedarsani:
Conflict-Aware Adversarial Training. CoRR abs/2410.16579 (2024) - 2023
- [j14]Zhuoling Li, Haohan Wang, Tymoteusz Swistek, En Yu, Haoqian Wang:
Efficient Few-Shot Classification via Contrastive Pretraining on Web Data. IEEE Trans. Artif. Intell. 4(3): 522-533 (2023) - [c38]Haohan Wang, Liang Liu, Boshen Zhang, Jiangning Zhang, Wuhao Zhang, Zhenye Gan, Yabiao Wang, Chengjie Wang, Haoqian Wang:
Calibrated Teacher for Sparsely Annotated Object Detection. AAAI 2023: 2519-2527 - [c37]Kun Xiang, Xing Zhang, Jinwen She, Jinpeng Liu, Haohan Wang, Shiqi Deng, Shancheng Jiang:
Toward Robust Diagnosis: A Contour Attention Preserving Adversarial Defense for COVID-19 Detection. AAAI 2023: 2928-2937 - [c36]Shufan Ming, Haohan Wang:
Self-learning for Annotating Website Privacy Policies at Scale. COMPSAC 2023: 1846-1851 - [c35]Zeyi Huang, Andy Zhou, Zijian Lin, Mu Cai, Haohan Wang, Yong Jae Lee:
A Sentence Speaks a Thousand Images: Domain Generalization through Distilling CLIP with Language Guidance. ICCV 2023: 11651-11661 - [c34]Haohan Wang:
Trustworthy Computing for Biomedical Challenges. ICHI 2023: 534-535 - [c33]Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He:
Optimizing the Collaboration Structure in Cross-Silo Federated Learning. ICML 2023: 1718-1736 - [c32]Jindong Wang, Haoliang Li, Haohan Wang, Sinno Jialin Pan, Xing Xie:
Trustworthy Machine Learning: Robustness, Generalization, and Interpretability. KDD 2023: 5827-5828 - [c31]Wenxuan Bao, Tianxin Wei, Haohan Wang, Jingrui He:
Adaptive Test-Time Personalization for Federated Learning. NeurIPS 2023 - [c30]Andy Zhou, Jindong Wang, Yu-Xiong Wang, Haohan Wang:
Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models. NeurIPS 2023 - [c29]Peiyan Zhang, Jiayan Guo, Chaozhuo Li, Yueqi Xie, Jaeboum Kim, Yan Zhang, Xing Xie, Haohan Wang, Sunghun Kim:
Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network. WSDM 2023: 168-176 - [i51]Haohan Wang, Liang Liu, Wuhao Zhang, Jiangning Zhang, Zhenye Gan, Yabiao Wang, Chengjie Wang, Haoqian Wang:
Iterative Few-shot Semantic Segmentation from Image Label Text. CoRR abs/2303.05646 (2023) - [i50]Haohan Wang, Liang Liu, Boshen Zhang, Jiangning Zhang, Wuhao Zhang, Zhenye Gan, Yabiao Wang, Chengjie Wang, Haoqian Wang:
Calibrated Teacher for Sparsely Annotated Object Detection. CoRR abs/2303.07582 (2023) - [i49]Jingfeng Zhang, Bo Song, Haohan Wang, Bo Han, Tongliang Liu, Lei Liu, Masashi Sugiyama:
BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise Learning. CoRR abs/2305.18377 (2023) - [i48]Mu Cai, Zeyi Huang, Yuheng Li, Haohan Wang, Yong Jae Lee:
Leveraging Large Language Models for Scalable Vector Graphics-Driven Image Understanding. CoRR abs/2306.06094 (2023) - [i47]Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He:
Optimizing the Collaboration Structure in Cross-Silo Federated Learning. CoRR abs/2306.06508 (2023) - [i46]Haoyang Liu, Maheep Chaudhary, Haohan Wang:
Towards Trustworthy and Aligned Machine Learning: A Data-centric Survey with Causality Perspectives. CoRR abs/2307.16851 (2023) - [i45]Peiyan Zhang, Haoyang Liu, Chaozhuo Li, Xing Xie, Sunghun Kim, Haohan Wang:
Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models. CoRR abs/2308.10632 (2023) - [i44]Zeyi Huang, Andy Zhou, Zijian Lin, Mu Cai, Haohan Wang, Yong Jae Lee:
A Sentence Speaks a Thousand Images: Domain Generalization through Distilling CLIP with Language Guidance. CoRR abs/2309.12530 (2023) - [i43]Yijiang Li, Ying Gao, Haohan Wang:
Understanding Adversarial Transferability in Federated Learning. CoRR abs/2310.00616 (2023) - [i42]Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, Yu-Xiong Wang:
Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models. CoRR abs/2310.04406 (2023) - [i41]Wang Lu, Hao Yu, Jindong Wang, Damien Teney, Haohan Wang, Yiqiang Chen, Qiang Yang, Xing Xie, Xiangyang Ji:
ZooPFL: Exploring Black-box Foundation Models for Personalized Federated Learning. CoRR abs/2310.05143 (2023) - [i40]Wenxuan Bao, Tianxin Wei, Haohan Wang, Jingrui He:
Adaptive Test-Time Personalization for Federated Learning. CoRR abs/2310.18816 (2023) - [i39]Andy Zhou, Jindong Wang, Yu-Xiong Wang, Haohan Wang:
Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models. CoRR abs/2311.01441 (2023) - [i38]Jixuan Leng, Yijiang Li, Haohan Wang:
Choosing Wisely and Learning Deeply: Selective Cross-Modality Distillation via CLIP for Domain Generalization. CoRR abs/2311.15145 (2023) - [i37]Tong Zhang, Haoyang Liu, Peiyan Zhang, Yuxuan Cheng, Haohan Wang:
Beyond Pixels: Exploring Human-Readable SVG Generation for Simple Images with Vision Language Models. CoRR abs/2311.15543 (2023) - [i36]Haoyang Liu, Tiancheng Xing, Luwei Li, Vibhu Dalal, Jingrui He, Haohan Wang:
Dataset Distillation via the Wasserstein Metric. CoRR abs/2311.18531 (2023) - [i35]Haohan Wang, Wei Feng, Yang Lu, Yaoyu Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junjie Shen, Zhangang Lin, Lixing Bo, Jingping Shao:
Generate E-commerce Product Background by Integrating Category Commonality and Personalized Style. CoRR abs/2312.13309 (2023) - 2022
- [j13]Haohan Wang, Bryon Aragam, Eric P. Xing:
Trade-offs of Linear Mixed Models in Genome-Wide Association Studies. J. Comput. Biol. 29(3): 233-242 (2022) - [j12]Haohan Wang, Oscar Lopez, Eric P. Xing, Wei Wu:
Kernel Mixed Model for Transcriptome Association Study. J. Comput. Biol. 29(12): 1353-1356 (2022) - [j11]Haohan Wang, Zhuoling Li, Haoqian Wang:
Few-Shot Steel Surface Defect Detection. IEEE Trans. Instrum. Meas. 71: 1-12 (2022) - [c28]Zeyi Huang, Haohan Wang, Dong Huang, Yong Jae Lee, Eric P. Xing:
The Two Dimensions of Worst-case Training and Their Integrated Effect for Out-of-domain Generalization. CVPR 2022: 9621-9631 - [c27]Haohan Wang, Liang Liu, Wuhao Zhang, Jiangning Zhang, Zhenye Gan, Yabiao Wang, Chengjie Wang, Haoqian Wang:
Iterative Few-shot Semantic Segmentation from Image Label Text. IJCAI 2022: 1385-1392 - [c26]Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing:
Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation. KDD 2022: 1846-1856 - [c25]Xuezhi Wang, Haohan Wang, Diyi Yang:
Measure and Improve Robustness in NLP Models: A Survey. NAACL-HLT 2022: 4569-4586 - [c24]Haohan Wang, Oscar L. Lopez, Wei Wu, Eric P. Xing:
Gene Set Priorization Guided by Regulatory Networks with p-values through Kernel Mixed Model. RECOMB 2022: 107-125 - [c23]Haohan Wang, Zeyi Huang, Hanlin Zhang, Yong Jae Lee, Eric P. Xing:
Toward learning human-aligned cross-domain robust models by countering misaligned features. UAI 2022: 2075-2084 - [i34]Zeyi Huang, Haohan Wang, Dong Huang, Yong Jae Lee, Eric P. Xing:
The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain Generalization. CoRR abs/2204.04384 (2022) - [i33]Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing:
Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation. CoRR abs/2206.01909 (2022) - [i32]Chonghan Chen, Qi Jiang, Chih-Hao Wang, Noel Chen, Haohan Wang, Xiang Li, Bhiksha Raj:
Bear the Query in Mind: Visual Grounding with Query-conditioned Convolution. CoRR abs/2206.09114 (2022) - [i31]Peiyan Zhang, Jiayan Guo, Chaozhuo Li, Yueqi Xie, Jaeboum Kim, Yan Zhang, Xing Xie, Haohan Wang, Sunghun Kim:
Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network. CoRR abs/2206.12781 (2022) - [i30]Yifan Zhong, Haohan Wang, Eric P. Xing:
MRCLens: an MRC Dataset Bias Detection Toolkit. CoRR abs/2207.08943 (2022) - [i29]Chonghan Chen, Haohan Wang, Leyang Hu, Yuhao Zhang, Shuguang Lyu, Jingcheng Wu, Xinnuo Li, Linjing Sun, Eric P. Xing:
Robustar: Interactive Toolbox Supporting Precise Data Annotation for Robust Vision Learning. CoRR abs/2207.08944 (2022) - [i28]Esla Timothy Anzaku, Haohan Wang, Arnout Van Messem, Wesley De Neve:
A Principled Evaluation Protocol for Comparative Investigation of the Effectiveness of DNN Classification Models on Similar-but-non-identical Datasets. CoRR abs/2209.01848 (2022) - [i27]Kun Xiang, Xing Zhang, Jinwen She, Jinpeng Liu, Haohan Wang, Shiqi Deng, Shancheng Jiang:
Toward Robust Diagnosis: A Contour Attention Preserving Adversarial Defense for COVID-19 Detection. CoRR abs/2211.16806 (2022) - [i26]Minh-Long Luu, Zeyi Huang, Eric P. Xing, Yong Jae Lee, Haohan Wang:
Expeditious Saliency-guided Mix-up through Random Gradient Thresholding. CoRR abs/2212.04875 (2022) - 2021
- [j10]Xuefeng Du, Haohan Wang, Zhenxi Zhu, Xiangrui Zeng, Yi-Wei Chang, Jing Zhang, Eric P. Xing, Min Xu:
Active learning to classify macromolecular structures in situ for less supervision in cryo-electron tomography. Bioinform. 37(16): 2340-2346 (2021) - [j9]Haohan Wang, Fen Pei, Michael M. Vanyukov, Ivet Bahar, Wei Wu, Eric P. Xing:
Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets. BMC Bioinform. 22(1): 50 (2021) - [j8]Songwei Ge, Haohan Wang, Amir Alavi, Eric P. Xing, Ziv Bar-Joseph:
Supervised Adversarial Alignment of Single-Cell RNA-seq Data. J. Comput. Biol. 28(5): 501-513 (2021) - [c22]Songwei Ge, Shlok Mishra, Chun-Liang Li, Haohan Wang, David Jacobs:
Robust Contrastive Learning Using Negative Samples with Diminished Semantics. NeurIPS 2021: 27356-27368 - [i25]Xuefeng Du, Haohan Wang, Zhenxi Zhu, Xiangrui Zeng, Yi-Wei Chang, Jing Zhang, Eric Poe Xing, Min Xu:
Active Learning to Classify Macromolecular Structures in situ for Less Supervision in Cryo-Electron Tomography. CoRR abs/2102.12040 (2021) - [i24]Zhuoling Li, Haohan Wang, Tymoteusz Swistek, Weixin Chen, Yuanzheng Li, Haoqian Wang:
Enabling the Network to Surf the Internet. CoRR abs/2102.12205 (2021) - [i23]Songwei Ge, Shlok Mishra, Haohan Wang, Chun-Liang Li, David Jacobs:
Robust Contrastive Learning Using Negative Samples with Diminished Semantics. CoRR abs/2110.14189 (2021) - [i22]Haohan Wang, Bryon Aragam, Eric P. Xing:
Tradeoffs of Linear Mixed Models in Genome-wide Association Studies. CoRR abs/2111.03739 (2021) - [i21]Haohan Wang, Zeyi Huang, Hanlin Zhang, Eric Poe Xing:
Toward Learning Human-aligned Cross-domain Robust Models by Countering Misaligned Features. CoRR abs/2111.03740 (2021) - [i20]Xuezhi Wang, Haohan Wang, Diyi Yang:
Measure and Improve Robustness in NLP Models: A Survey. CoRR abs/2112.08313 (2021) - 2020
- [j7]Yumin Zheng, Haohan Wang, Yang Zhang, Xin Gao, Eric P. Xing, Min Xu:
Poly(A)-DG: A deep-learning-based domain generalization method to identify cross-species Poly(A) signal without prior knowledge from target species. PLoS Comput. Biol. 16(11): 1008297 (2020) - [c21]Haohan Wang, Xindi Wu, Zeyi Huang, Eric P. Xing:
High-Frequency Component Helps Explain the Generalization of Convolutional Neural Networks. CVPR 2020: 8681-8691 - [c20]Zeyi Huang, Haohan Wang, Eric P. Xing, Dong Huang:
Self-challenging Improves Cross-Domain Generalization. ECCV (2) 2020: 124-140 - [c19]Songwei Ge, Haohan Wang, Amir Alavi, Eric P. Xing, Ziv Bar-Joseph:
Supervised Adversarial Alignment of Single-Cell RNA-seq Data. RECOMB 2020: 72-87 - [i19]Zeyi Huang, Haohan Wang, Eric P. Xing, Dong Huang:
Self-Challenging Improves Cross-Domain Generalization. CoRR abs/2007.02454 (2020) - [i18]Haohan Wang, Peiyan Zhang, Eric P. Xing:
Word Shape Matters: Robust Machine Translation with Visual Embedding. CoRR abs/2010.09997 (2020) - [i17]Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing:
Squared 𝓁2 Norm as Consistency Loss for Leveraging Augmented Data to Learn Robust and Invariant Representations. CoRR abs/2011.13052 (2020)
2010 – 2019
- 2019
- [j6]Haohan Wang, Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing:
Precision Lasso: accounting for correlations and linear dependencies in high-dimensional genomic data. Bioinform. 35(7): 1181-1187 (2019) - [j5]Haohan Wang, Tianwei Yue, Jingkang Yang, Wei Wu, Eric P. Xing:
Deep mixed model for marginal epistasis detection and population stratification correction in genome-wide association studies. BMC Bioinform. 20-S(23): 656 (2019) - [j4]Ming Xu, Jianping Wu, Mengqi Liu, Yunpeng Xiao, Haohan Wang, Dongmei Hu:
Discovery of Critical Nodes in Road Networks Through Mining From Vehicle Trajectories. IEEE Trans. Intell. Transp. Syst. 20(2): 583-593 (2019) - [j3]Ming Xu, Jianping Wu, Haohan Wang, Mengxin Cao:
Anomaly Detection in Road Networks Using Sliding-Window Tensor Factorization. IEEE Trans. Intell. Transp. Syst. 20(12): 4704-4713 (2019) - [c18]Haohan Wang, Da Sun, Eric P. Xing:
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. AAAI 2019: 7136-7143 - [c17]He He, Sheng Zha, Haohan Wang:
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual. DeepLo@EMNLP-IJCNLP 2019: 132-142 - [c16]Xindi Wu, Yijun Mao, Haohan Wang, Xiangrui Zeng, Xin Gao, Eric P. Xing, Min Xu:
Regularized Adversarial Training (RAT) for Robust Cellular Electron Cryo Tomograms Classification. BIBM 2019: 1-6 - [c15]Haohan Wang, Changpeng Lu, Wei Wu, Eric P. Xing:
Graph-structured Sparse Mixed Models for Genetic Association with Confounding Factors Correction. BIBM 2019: 298-302 - [c14]Haohan Wang, Yibing Wei, Mengxin Cao, Ming Xu, Wei Wu, Eric P. Xing:
Deep Inductive Matrix Completion for Biomedical Interaction Prediction. BIBM 2019: 520-527 - [c13]Haohan Wang, Zexue He, Zachary C. Lipton, Eric P. Xing:
Learning Robust Representations by Projecting Superficial Statistics Out. ICLR 2019 - [c12]Haohan Wang, Songwei Ge, Zachary C. Lipton, Eric P. Xing:
Learning Robust Global Representations by Penalizing Local Predictive Power. NeurIPS 2019: 10506-10518 - [c11]Haohan Wang, Zhenglin Wu, Eric P. Xing:
Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications. PSB 2019: 54-65 - [c10]Haohan Wang, Xiang Liu, Yifeng Tao, Wenting Ye, Qiao Jin, William W. Cohen, Eric P. Xing:
Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning. PSB 2019: 112-123 - [i16]Haohan Wang, Zexue He, Zachary C. Lipton, Eric P. Xing:
Learning Robust Representations by Projecting Superficial Statistics Out. CoRR abs/1903.06256 (2019) - [i15]Haohan Wang, Xindi Wu, Pengcheng Yin, Eric P. Xing:
High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks. CoRR abs/1905.13545 (2019) - [i14]Haohan Wang, Songwei Ge, Eric P. Xing, Zachary C. Lipton:
Learning Robust Global Representations by Penalizing Local Predictive Power. CoRR abs/1905.13549 (2019) - [i13]He He, Sheng Zha, Haohan Wang:
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual. CoRR abs/1908.10763 (2019) - 2018
- [j2]Yunpeng Xiao, Xixi Li, Haohan Wang, Ming Xu, Yanbing Liu:
3-HBP: A Three-Level Hidden Bayesian Link Prediction Model in Social Networks. IEEE Trans. Comput. Soc. Syst. 5(2): 430-443 (2018) - [c9]Yifeng Chen, Wei Sun, Haohan Wang:
Heterogeneous Hi-C Data Super-resolution with a Conditional Generative Adversarial Network. BIBM 2018: 2213-2220 - [c8]Yunpeng Xiao, Liangyun Liu, Ming Xu, Haohan Wang, Yanbing Liu:
GLDA-FP: Gaussian LDA Model for Forward Prediction. BigData Congress 2018: 124-139 - [i12]Tianwei Yue, Haohan Wang:
Deep Learning for Genomics: A Concise Overview. CoRR abs/1802.00810 (2018) - [i11]Zhenglin Wu, Haohan Wang, Mingze Cao, Yin Chen, Eric P. Xing:
Fair Deep Learning Prediction for Healthcare Applications with Confounder Filtering. CoRR abs/1803.07276 (2018) - [i10]Haohan Wang, Da Sun, Eric P. Xing:
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. CoRR abs/1809.02719 (2018) - 2017
- [j1]Haohan Wang, Aman Gupta, Ming Xu:
Extracting compact representation of knowledge from gene expression data for protein-protein interaction. Int. J. Data Min. Bioinform. 17(4): 279-292 (2017) - [c7]Haohan Wang, Xiang Liu, Yunpeng Xiao, Ming Xu, Eric P. Xing:
Multiplex confounding factor correction for genomic association mapping with squared sparse linear mixed model. BIBM 2017: 194-201 - [c6]Haohan Wang, Bryon Aragam, Eric P. Xing:
Variable selection in heterogeneous datasets: A truncated-rank sparse linear mixed model with applications to genome-wide association studies. BIBM 2017: 431-438 - [c5]Haohan Wang, Aaksha Meghawat, Louis-Philippe Morency, Eric P. Xing:
Select-additive learning: Improving generalization in multimodal sentiment analysis. ICME 2017: 949-954 - [i9]Haohan Wang, Bhiksha Raj, Eric P. Xing:
On the Origin of Deep Learning. CoRR abs/1702.07800 (2017) - [i8]Wenting Ye, Xiang Liu, Haohan Wang, Eric P. Xing:
A Sparse Graph-Structured Lasso Mixed Model for Genetic Association with Confounding Correction. CoRR abs/1711.04162 (2017) - 2016
- [c4]Haohan Wang, Jingkang Yang:
Multiple confounders correction with regularized linear mixed effect models, with application in biological processes. BIBM 2016: 1561-1568 - [i7]Haohan Wang, Aaksha Meghawat, Louis-Philippe Morency, Eric P. Xing:
Select-Additive Learning: Improving Cross-individual Generalization in Multimodal Sentiment Analysis. CoRR abs/1609.05244 (2016) - [i6]Jingkang Yang, Haohan Wang, Jun Zhu, Eric P. Xing:
SeDMiD for Confusion Detection: Uncovering Mind State from Time Series Brain Wave Data. CoRR abs/1611.10252 (2016) - 2015
- [c3]Aman Gupta, Haohan Wang, Madhavi K. Ganapathiraju:
Learning structure in gene expression data using deep architectures, with an application to gene clustering. BIBM 2015: 1328-1335 - [i5]Haohan Wang, Madhavi K. Ganapathiraju:
Evaluation of Protein-protein Interaction Predictors with Noisy Partially Labeled Data Sets. CoRR abs/1509.05742 (2015) - [i4]Haohan Wang, Bhiksha Raj:
A Survey: Time Travel in Deep Learning Space: An Introduction to Deep Learning Models and How Deep Learning Models Evolved from the Initial Ideas. CoRR abs/1510.04781 (2015) - [i3]Haohan Wang, Madhavi K. Ganapathiraju:
Evaluating Protein-protein Interaction Predictors with a Novel 3-Dimensional Metric. CoRR abs/1511.02196 (2015) - 2014
- [i2]Ming Xu, Jianping Wu, Yiman Du, Haohan Wang, Geqi Qi, Kezhen Hu, Yunpeng Xiao:
Discovery of Important Crossroads in Road Network using Massive Taxi Trajectories. CoRR abs/1407.2506 (2014) - [i1]Seungwhan Moon, Suyoun Kim, Haohan Wang:
Multimodal Transfer Deep Learning for Audio Visual Recognition. CoRR abs/1412.3121 (2014) - 2013
- [c2]Haohan Wang, Yiwei Li, Xiaobo Hu, Yucong Yang, Zhu Meng, Kai-Min Chang:
Using EEG to Improve Massive Open Online Courses Feedback Interaction. AIED Workshops 2013 - [c1]Haohan Wang, Agha Ali Raza, Yibin Lin, Roni Rosenfeld:
Behavior analysis of low-literate users of a viral speech-based telephone service. ACM DEV (4) 2013: 12:1-12:9
Coauthor Index
Eric P. Xing
aka: Eric Poe Xing
aka: Eric Poe Xing
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