He Zhao

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 71

Top Topics

Meta Information

Document Summarization

Relational Data

Top Venues

Publications

He Zhao, Edwin V. Bonilla
Bayesian Factorised Granger-Causal Graphs For Multivariate Time-series Data. CoRR (2024)
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 (2024)
Edwin V. Bonilla, Pantelis Elinas, He Zhao, Maurizio Filippone, Vassili Kitsios, Terry O'Kane
Variational DAG Estimation via State Augmentation With Stochastic Permutations. CoRR (2024)
Hangting Ye, Wei Fan, Xiaozhuang Song, Shun Zheng, He Zhao, Dandan Guo, Yi Chang
PTaRL: Prototype-based Tabular Representation Learning via Space Calibration. CoRR (2024)
Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Q. Phung
Optimal Transport for Structure Learning Under Missing Data. CoRR (2024)
Myong Chol Jung, He Zhao, Joanna Dipnall, Belinda Gabbe, Lan Du
Enhancing Near OOD Detection in Prompt Learning: Maximum Gains, Minimal Costs. CoRR (2024)
Xuesong Wang, He Zhao, Edwin V. Bonilla
Rényi Neural Processes. CoRR (2024)
He Zhao, Ke Sun, Amir Dezfouli, Edwin V. Bonilla
Transformed Distribution Matching for Missing Value Imputation. CoRR (2023)
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 (2023)
Long Tung Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung
Vector Quantized Wasserstein Auto-Encoder. ICML (2023)
He Zhao, Ke Sun, Amir Dezfouli, Edwin V. Bonilla
Transformed Distribution Matching for Missing Value Imputation. ICML (2023)
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)
Myong Chol Jung, He Zhao, Joanna Dipnall, Lan Du
Beyond Unimodal: Generalising Neural Processes for Multimodal Uncertainty Estimation. NeurIPS (2023)
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 (2023)
Son Duy Dao, Dat Huynh, He Zhao, Dinh Phung, Jianfei Cai
Open-Vocabulary Multi-label Image Classification with Pretrained Vision-Language Model. ICME (2023)
Tung-Long Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung
Vector Quantized Wasserstein Auto-Encoder. CoRR (2023)
Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin Bonilla, Dinh Q. Phung
Learning Directed Graphical Models with Optimal Transport. CoRR (2023)
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)
Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Phung
Adversarial local distribution regularization for knowledge distillation. WACV (2023)
Son Duy Dao, He Zhao, Dinh Q. Phung, Jianfei Cai
Contrastively enforcing distinctiveness for multi-label image classification. Neurocomputing 555 (2023)
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)
Dandan Guo, Long Tian, He Zhao, Mingyuan Zhou, Hongyuan Zha
Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport. NeurIPS (2022)
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)
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)
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)
Dandan Guo, Long Tian, He Zhao, Mingyuan Zhou, Hongyuan Zha
Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport. CoRR (2022)
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 (2022)
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)
Anh Tuan Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. ICLR (2022)
Dandan Guo, Zhuo Li, Meixi Zheng, He Zhao, Mingyuan Zhou, Hongyuan Zha
Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification. CoRR (2022)
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 (2022)
Tuan Anh Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. CoRR (2022)
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)
Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin Bonilla, Gholamreza Haffari, Dinh Q. Phung
Learning to Counter: Stochastic Feature-based Learning for Diverse Counterfactual Explanations. CoRR (2022)
Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Q. Phung
Particle-based Adversarial Local Distribution Regularization. AISTATS (2022)
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)
He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L. Buntine
Neural Topic Model via Optimal Transport. ICLR (2021)
Yuan Jin, He Zhao, Ming Liu, Lan Du, Wray L. Buntine
Neural Attention-Aware Hierarchical Topic Model. EMNLP (1) (2021)
Mahmoud Hossam, Trung Le, He Zhao, Viet Huynh, Dinh Phung
Improved and Efficient Text Adversarial Attacks using Target Information. CoRR (2021)
He Zhao, Dinh Q. Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine
Topic Modelling Meets Deep Neural Networks: A Survey. IJCAI (2021)
Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Seyit Camtepe, Dinh Phung
Understanding and Achieving Efficient Robustness with Adversarial Contrastive Learning. CoRR (2021)
Viet Huynh, Dinh Q. Phung, He Zhao
Optimal Transport for Deep Generative Models: State of the Art and Research Challenges. IJCAI (2021)
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)
Yuan Jin, He Zhao, Ming Liu, Lan Du, Wray L. Buntine
Neural Attention-Aware Hierarchical Topic Model. CoRR (2021)
He Zhao, Dinh Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine
Topic Modelling Meets Deep Neural Networks: A Survey. CoRR (2021)
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 (2020)
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 (2020)
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)
He Zhao, Trung Le, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung
Towards Understanding Pixel Vulnerability under Adversarial Attacks for Images. CoRR (2020)
Mahmoud Hossam, Trung Le, He Zhao, Dinh Phung
Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability. ICPR (2020)
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 (2020)
Thanh Nguyen-Duc, He Zhao, Jianfei Cai, Dinh Phung
MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models. CoRR (2020)
Viet Huynh, He Zhao, Dinh Phung
OTLDA: A Geometry-aware Optimal Transport Approach for Topic Modeling. NeurIPS (2020)
He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L. Buntine
Neural Sinkhorn Topic Model. CoRR (2020)
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)
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 (2020)
He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Dinh Phung, Mingyuan Zhou
Variational Autoencoders for Sparse and Overdispersed Discrete Data. AISTATS (2020)
Mahmoud Hossam, Trung Le, He Zhao, Dinh Phung
Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability. CoRR (2020)
He Zhao, Lan Du, Wray L. Buntine, Gang Liu
Leveraging external information in topic modelling. Knowl. Inf. Syst. 61 (2) (2019)
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 (2019)
He Zhao, Lan Du, Guanfeng Liu, Wray L. Buntine
Leveraging Meta Information in Short Text Aggregation. ACL (1) (2019)
He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Mingyuan Zhou
Variational Autoencoders for Sparse and Overdispersed Discrete Data. CoRR (2019)
He Zhao, Lan Du, Wray L. Buntine, Mingyuan Zhou
Dirichlet belief networks for topic structure learning. NeurIPS (2018)
He Zhao, Piyush Rai, Lan Du, Wray L. Buntine
Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences. AISTATS (2018)
He Zhao, Lan Du, Wray L. Buntine, Mingyuan Zhou
Dirichlet belief networks for topic structure learning. CoRR (2018)
He Zhao, Lan Du, Wray L. Buntine, Mingyuan Zhou
Inter and Intra Topic Structure Learning with Word Embeddings. ICML (2018)
He Zhao, Lan Du, Wray L. Buntine
Leveraging Node Attributes for Incomplete Relational Data. CoRR (2017)
He Zhao, Lan Du, Wray L. Buntine
Leveraging Node Attributes for Incomplete Relational Data. ICML (2017)
He Zhao, Lan Du, Wray L. Buntine
A Word Embeddings Informed Focused Topic Model. ACML (2017)
He Zhao, Lan Du, Wray L. Buntine, Gang Liu
MetaLDA: a Topic Model that Efficiently Incorporates Meta information. CoRR (2017)
He Zhao, Lan Du, Wray L. Buntine, Gang Liu
MetaLDA: A Topic Model that Efficiently Incorporates Meta Information. ICDM (2017)