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ORCIDHaohan Wang
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2020 – today
- 2021
[j7]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)- [i21]Xuefeng Du, Haohan Wang, Zhenxi Zhu, Xiangrui Zeng, Yi-Wei Chang, Jing Zhang, Eric Po Xing, Min Xu:
Active Learning to Classify Macromolecular Structures in situ for Less Supervision in Cryo-Electron Tomography. CoRR abs/2102.12040 (2021) - [i20]Zhuoling Li, Haohan Wang, Tymoteusz Swistek, Weixin Chen, Yuanzheng Li, Haoqian Wang:
Enabling the Network to Surf the Internet. CoRR abs/2102.12205 (2021) - 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
aka: Eric Po Xing
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