default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDHe Zhao 0001
Ethan Zhao 0001
Person information
- affiliation (PhD 2019): Monash University, Faculty of Information Technology, Melbourne, Australia
Other persons with the same name
- He Zhao — disambiguation page
- He Zhao 0002
![[0000-0002-8264-9297]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-8264-9297")
— Beijing Institute of Technology, Beijing, China (and 1 more) - He Zhao 0003 — Beijing Institute of Technology, School of Computer Science and Technology, Beijing, China
- He Zhao 0004 — York University, Department of Electrical Engineering and Computer Science, Toronto, Canada
- He Zhao 0005 — China National Institute of Standardization, Beijing, China
- He Zhao 0006 — Peking University, School of EECS, Key Laboratory of Machine Perception, Beijing, China
- He Zhao 0007 — University of Waterloo, Department of Geography and Environmental Management, Waterloo, Canada
- He Zhao 0008 — Nanjing University, School of Electronic Science and Engineering, Nanjing, China
- He Zhao 0009 — Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Shenzhen, China
- He Zhao 0010 — Jilin Agricultural Science and Technology University, Jilin, China
- He Zhao 0011 — Chinese Academy of Sciences, Hefei Institutes of Physical Science, Hefei, China
- He Zhao 0012 — MathWorks, Inc., Natick, MA, USA (and 1 more)
- He Zhao 0013 — Northeastern University, College of Information Science and Engineering, Shenyang, China
- Ethan Zhao 0002 — Tencent Music Entertainment, Shenzhen, China
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
Books and Theses
- 2019
[b1]He Zhao:
Structured Bayesian Latent Factor Models with Meta-data. Monash University, Australia, 2019
Journal Articles
- 2023
- [j3]Son Duy Dao, He Zhao, Dinh Q. Phung, Jianfei Cai:
Contrastively enforcing distinctiveness for multi-label image classification. Neurocomputing 555: 126605 (2023) - [j2]Anh Tuan Bui, Trung Le, He Zhao, Quan Hung Tran, Paul Montague, Dinh Phung:
Generating Adversarial Examples with Task Oriented Multi-Objective Optimization. Trans. Mach. Learn. Res. 2023 (2023) - 2019
- [j1]He Zhao, Lan Du, Wray L. Buntine, Gang Liu:
Leveraging external information in topic modelling. Knowl. Inf. Syst. 61(2): 661-693 (2019)
Conference and Workshop Papers
- 2024
- [c39]Hangting Ye, Wei Fan, Xiaozhuang Song, Shun Zheng, He Zhao, Dandan Guo, Yi Chang:
PTaRL: Prototype-based Tabular Representation Learning via Space Calibration. ICLR 2024 - [c38]Jintong Gao, He Zhao, Dandan Guo, Hongyuan Zha:
Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification. ICML 2024 - [c37]Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Phung:
Optimal Transport for Structure Learning Under Missing Data. ICML 2024 - [c36]Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin V. Bonilla, Dinh Phung:
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport. ICML 2024 - 2023
- [c35]Son Duy Dao, Dat Huynh, He Zhao, Dinh Phung, Jianfei Cai:
Open-Vocabulary Multi-label Image Classification with Pretrained Vision-Language Model. ICME 2023: 2135-2140 - [c34]Long Tung Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung:
Vector Quantized Wasserstein Auto-Encoder. ICML 2023: 35223-35242 - [c33]He Zhao, Ke Sun, Amir Dezfouli, Edwin V. Bonilla:
Transformed Distribution Matching for Missing Value Imputation. ICML 2023: 42159-42186 - [c32]Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin V. Bonilla, Gholamreza Haffari, Dinh Q. Phung:
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations. KDD 2023: 2211-2222 - [c31]Thanh Nguyen-Duc, Trung Le, Roland Bammer, He Zhao, Jianfei Cai, Dinh Q. Phung:
Cross-Adversarial Local Distribution Regularization for Semi-supervised Medical Image Segmentation. MICCAI (1) 2023: 183-194 - [c30]Jintong Gao, He Zhao, Zhuo Li, Dandan Guo:
Enhancing Minority Classes by Mixing: An Adaptative Optimal Transport Approach for Long-tailed Classification. NeurIPS 2023 - [c29]Myong Chol Jung, He Zhao, Joanna Dipnall, Lan Du:
Beyond Unimodal: Generalising Neural Processes for Multimodal Uncertainty Estimation. NeurIPS 2023 - [c28]Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Phung:
Adversarial local distribution regularization for knowledge distillation. WACV 2023: 4670-4679 - 2022
- [c27]Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Q. Phung:
Particle-based Adversarial Local Distribution Regularization. AISTATS 2022: 5212-5224 - [c26]Trung Le, Anh Tuan Bui, Le Minh Tri Tue, He Zhao, Paul Montague, Quan Hung Tran, Dinh Q. Phung:
On Global-view Based Defense via Adversarial Attack and Defense Risk Guaranteed Bounds. AISTATS 2022: 11438-11460 - [c25]Dongsheng Wang, Dandan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen, Mingyuan Zhou:
Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings. ICLR 2022 - [c24]Anh Tuan Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung:
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. ICLR 2022 - [c23]Thanh Nguyen-Duc, He Zhao, Jianfei Cai, Dinh Phung:
MED-TEX: Transfer and Explain Knowledge with Less Data from Pretrained Medical Imaging Models. ISBI 2022: 1-4 - [c22]Dandan Guo, Zhuo Li, Meixi Zheng, He Zhao, Mingyuan Zhou, Hongyuan Zha:
Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification. NeurIPS 2022 - [c21]Dandan Guo, Long Tian, He Zhao, Mingyuan Zhou, Hongyuan Zha:
Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport. NeurIPS 2022 - [c20]Myong Chol Jung, He Zhao, Joanna Dipnall, Belinda Gabbe, Lan Du:
Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture. NeurIPS 2022 - [c19]Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Q. Phung:
Cycle class consistency with distributional optimal transport and knowledge distillation for unsupervised domain adaptation. UAI 2022: 1519-1529 - 2021
- [c18]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung:
Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness. AAAI 2021: 6831-6839 - [c17]Yuan Jin, He Zhao, Ming Liu, Lan Du, Wray L. Buntine:
Neural Attention-Aware Hierarchical Topic Model. EMNLP (1) 2021: 1042-1052 - [c16]He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L. Buntine:
Neural Topic Model via Optimal Transport. ICLR 2021 - [c15]Viet Huynh, Dinh Q. Phung, He Zhao:
Optimal Transport for Deep Generative Models: State of the Art and Research Challenges. IJCAI 2021: 4450-4457 - [c14]He Zhao, Dinh Q. Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine:
Topic Modelling Meets Deep Neural Networks: A Survey. IJCAI 2021: 4713-4720 - [c13]Tuan Nguyen, Trung Le, He Zhao, Quan Hung Tran, Truyen Nguyen, Dinh Q. Phung:
Most: multi-source domain adaptation via optimal transport for student-teacher learning. UAI 2021: 225-235 - 2020
- [c12]He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Dinh Phung, Mingyuan Zhou:
Variational Autoencoders for Sparse and Overdispersed Discrete Data. AISTATS 2020: 1684-1694 - [c11]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. DeVel, Tamas Abraham, Dinh Q. Phung:
Improving Adversarial Robustness by Enforcing Local and Global Compactness. ECCV (27) 2020: 209-223 - [c10]Mahmoud Hossam, Trung Le, He Zhao, Dinh Phung:
Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability. ICPR 2020: 8922-8928 - [c9]Viet Huynh, He Zhao, Dinh Phung:
OTLDA: A Geometry-aware Optimal Transport Approach for Topic Modeling. NeurIPS 2020 - [c8]Jinming Zhao, Ming Liu, Longxiang Gao, Yuan Jin, Lan Du, He Zhao, He Zhang, Gholamreza Haffari:
SummPip: Unsupervised Multi-Document Summarization with Sentence Graph Compression. SIGIR 2020: 1949-1952 - 2019
- [c7]He Zhao, Lan Du, Guanfeng Liu, Wray L. Buntine:
Leveraging Meta Information in Short Text Aggregation. ACL (1) 2019: 4042-4049 - 2018
- [c6]He Zhao, Piyush Rai, Lan Du, Wray L. Buntine:
Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences. AISTATS 2018: 1943-1951 - [c5]He Zhao, Lan Du, Wray L. Buntine, Mingyuan Zhou:
Inter and Intra Topic Structure Learning with Word Embeddings. ICML 2018: 5887-5896 - [c4]He Zhao, Lan Du, Wray L. Buntine, Mingyuan Zhou:
Dirichlet belief networks for topic structure learning. NeurIPS 2018: 7966-7977 - 2017
- [c3]He Zhao, Lan Du, Wray L. Buntine:
A Word Embeddings Informed Focused Topic Model. ACML 2017: 423-438 - [c2]He Zhao, Lan Du, Wray L. Buntine, Gang Liu:
MetaLDA: A Topic Model that Efficiently Incorporates Meta Information. ICDM 2017: 635-644 - [c1]He Zhao, Lan Du, Wray L. Buntine:
Leveraging Node Attributes for Incomplete Relational Data. ICML 2017: 4072-4081
Informal and Other Publications
- 2024
- [i40]Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Q. Phung:
A Class-aware Optimal Transport Approach with Higher-Order Moment Matching for Unsupervised Domain Adaptation. CoRR abs/2401.15952 (2024) - [i39]Edwin V. Bonilla, Pantelis Elinas, He Zhao, Maurizio Filippone, Vassili Kitsios, Terry O'Kane:
Variational DAG Estimation via State Augmentation With Stochastic Permutations. CoRR abs/2402.02644 (2024) - [i38]He Zhao, Edwin V. Bonilla:
Bayesian Factorised Granger-Causal Graphs For Multivariate Time-series Data. CoRR abs/2402.03614 (2024) - [i37]Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Q. Phung:
Optimal Transport for Structure Learning Under Missing Data. CoRR abs/2402.15255 (2024) - [i36]Zhuo Li, He Zhao, Zhen Li, Tongliang Liu, Dandan Guo, Xiang Wan:
Extracting Clean and Balanced Subset for Noisy Long-tailed Classification. CoRR abs/2404.06795 (2024) - [i35]Xuesong Wang, He Zhao, Edwin V. Bonilla:
Rényi Neural Processes. CoRR abs/2405.15991 (2024) - [i34]Myong Chol Jung, He Zhao, Joanna Dipnall, Belinda Gabbe, Lan Du:
Enhancing Near OOD Detection in Prompt Learning: Maximum Gains, Minimal Costs. CoRR abs/2405.16091 (2024) - [i33]Xiaohao Yang, He Zhao, Dinh Q. Phung, Wray L. Buntine, Lan Du:
LLM Reading Tea Leaves: Automatically Evaluating Topic Models with Large Language Models. CoRR abs/2406.09008 (2024) - [i32]Hangting Ye, Wei Fan, Xiaozhuang Song, Shun Zheng, He Zhao, Dandan Guo, Yi Chang:
PTaRL: Prototype-based Tabular Representation Learning via Space Calibration. CoRR abs/2407.05364 (2024) - 2023
- [i31]Tung-Long Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung:
Vector Quantized Wasserstein Auto-Encoder. CoRR abs/2302.05917 (2023) - [i30]He Zhao, Ke Sun, Amir Dezfouli, Edwin V. Bonilla:
Transformed Distribution Matching for Missing Value Imputation. CoRR abs/2302.10363 (2023) - [i29]Myong Chol Jung, He Zhao, Joanna Dipnall, Belinda Gabbe, Lan Du:
Multimodal Neural Processes for Uncertainty Estimation. CoRR abs/2304.01518 (2023) - [i28]Anh Tuan Bui, Trung Le, He Zhao, Quan Hung Tran, Paul Montague, Dinh Q. Phung:
Generating Adversarial Examples with Task Oriented Multi-Objective Optimization. CoRR abs/2304.13229 (2023) - [i27]Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin V. Bonilla, Dinh Q. Phung:
Learning Directed Graphical Models with Optimal Transport. CoRR abs/2305.15927 (2023) - [i26]Xiaohao Yang, He Zhao, Dinh Phung, Lan Du:
Towards Generalising Neural Topical Representations. CoRR abs/2307.12564 (2023) - [i25]Thanh Nguyen-Duc, Trung Le, Roland Bammer, He Zhao, Jianfei Cai, Dinh Q. Phung:
Cross-adversarial local distribution regularization for semi-supervised medical image segmentation. CoRR abs/2310.01176 (2023) - 2022
- [i24]Tuan-Anh Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung:
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. CoRR abs/2202.13437 (2022) - [i23]Dongsheng Wang, Dandan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen, Mingyuan Zhou:
Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings. CoRR abs/2203.01570 (2022) - [i22]Dandan Guo, Zhuo Li, Meixi Zheng, He Zhao, Mingyuan Zhou, Hongyuan Zha:
Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification. CoRR abs/2208.02951 (2022) - [i21]Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin V. Bonilla, Gholamreza Haffari, Dinh Q. Phung:
Learning to Counter: Stochastic Feature-based Learning for Diverse Counterfactual Explanations. CoRR abs/2209.13446 (2022) - [i20]Myong Chol Jung, He Zhao, Joanna Dipnall, Belinda Gabbe, Lan Du:
Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture. CoRR abs/2210.02676 (2022) - [i19]Dandan Guo, Long Tian, He Zhao, Mingyuan Zhou, Hongyuan Zha:
Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport. CoRR abs/2210.04144 (2022) - 2021
- [i18]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Seyit Camtepe, Dinh Phung:
Understanding and Achieving Efficient Robustness with Adversarial Contrastive Learning. CoRR abs/2101.10027 (2021) - [i17]He Zhao, Dinh Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine:
Topic Modelling Meets Deep Neural Networks: A Survey. CoRR abs/2103.00498 (2021) - [i16]Mahmoud Hossam, Trung Le, He Zhao, Viet Huynh, Dinh Phung:
Improved and Efficient Text Adversarial Attacks using Target Information. CoRR abs/2104.13484 (2021) - [i15]Son Duy Dao, Ethan Zhao, Dinh Phung, Jianfei Cai:
Multi-Label Image Classification with Contrastive Learning. CoRR abs/2107.11626 (2021) - [i14]Yuan Jin, He Zhao, Ming Liu, Lan Du, Wray L. Buntine:
Neural Attention-Aware Hierarchical Topic Model. CoRR abs/2110.07161 (2021) - 2020
- [i13]Yuan Jin, He Zhao, Ming Liu, Lan Du, Yunfeng Li, Ruohua Xu, Longxiang Gao:
Leveraging Cross Feedback of User and Item Embeddings for Variational Autoencoder based Collaborative Filtering. CoRR abs/2002.09145 (2020) - [i12]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. DeVel, Tamas Abraham, Dinh Phung:
Improving Adversarial Robustness by Enforcing Local and Global Compactness. CoRR abs/2007.05123 (2020) - [i11]Jinming Zhao, Ming Liu, Longxiang Gao, Yuan Jin, Lan Du, He Zhao, He Zhang, Gholamreza Haffari:
SummPip: Unsupervised Multi-Document Summarization with Sentence Graph Compression. CoRR abs/2007.08954 (2020) - [i10]Thanh Nguyen-Duc, He Zhao, Jianfei Cai, Dinh Phung:
MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models. CoRR abs/2008.02593 (2020) - [i9]He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L. Buntine:
Neural Sinkhorn Topic Model. CoRR abs/2008.13537 (2020) - [i8]Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. DeVel, Tamas Abraham, Dinh Phung:
Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness. CoRR abs/2009.09612 (2020) - [i7]He Zhao, Trung Le, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung:
Towards Understanding Pixel Vulnerability under Adversarial Attacks for Images. CoRR abs/2010.06131 (2020) - [i6]Mahmoud Hossam, Trung Le, He Zhao, Dinh Phung:
Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability. CoRR abs/2010.06812 (2020) - 2019
- [i5]He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Mingyuan Zhou:
Variational Autoencoders for Sparse and Overdispersed Discrete Data. CoRR abs/1905.00616 (2019) - [i4]He Zhao, Trung Le, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung:
Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions. CoRR abs/1910.01329 (2019) - 2018
- [i3]He Zhao, Lan Du, Wray L. Buntine, Mingyuan Zhou:
Dirichlet belief networks for topic structure learning. CoRR abs/1811.00717 (2018) - 2017
- [i2]He Zhao, Lan Du, Wray L. Buntine:
Leveraging Node Attributes for Incomplete Relational Data. CoRR abs/1706.04289 (2017) - [i1]He Zhao, Lan Du, Wray L. Buntine, Gang Liu:
MetaLDA: a Topic Model that Efficiently Incorporates Meta information. CoRR abs/1709.06365 (2017)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-09-10 02:11 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
