He Zhao - RankMe

119 papers A* 31A 8B 1C 1Journal 69Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Calibrating Tabular Anomaly Detection via Optimal Transport. CoRR Hangting Ye, He Zhao, Wei Fan, Xiaozhuang Song, Dandan Guo, Yi Chang, Hongyuan Zha
2026	J	`jnl`	Causal Preference Elicitation. CoRR Edwin V. Bonilla, He Zhao, Daniel M. Steinberg
2026	J	`jnl`	Deep Tabular Representation Corrector. CoRR Hangting Ye, Peng Wang, Wei Fan, Xiaozhuang Song, He Zhao, Dandan Gun, Yi Chang
2026	J	`jnl`	Deep Tabular Representation Corrector. IEEE Trans. Pattern Anal. Mach. Intell. Hangting Ye, Peng Wang, Wei Fan, Xiaozhuang Song, He Zhao, Dandan Guo, Yi Chang
2026	J	`jnl`	Deep neural network calibration by reducing classifier shift with stochastic masking. Pattern Recognit. Jiani Ni, He Zhao, Yibo Yang, Dandan Guo
2026	J	`jnl`	HiBaNG: Hierarchical Bayesian Nonparametric Granger Causal Discovery in Low-Data Regimes. Trans. Mach. Learn. Res. He Zhao, Vassili Kitsios, Terence J. O'Kane, Edwin V. Bonilla
2026	J	`jnl`	Near OOD Detection for Vision-Language Prompt Learning with Contrastive Logit Score. Int. J. Comput. Vis. Myong Chol Jung, Joanna Dipnall, Belinda Gabbe, He Zhao
2026	J	`jnl`	Ordering-based Causal Discovery via Generalized Score Matching. CoRR Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Phung
2026	J	`jnl`	Safeguarding LLM Fine-tuning via Push-Pull Distributional Alignment. CoRR Haozhong Wang, Zhuo Li, Yibo Yang, He Zhao, Hongyuan Zha, Dandan Guo
2026	J	`jnl`	Unifying Stable Optimization and Reference Regularization in RLHF. CoRR Li He, Qiang Qu, He Zhao, Stephen Wan, Dadong Wang, Lina Yao, Tongliang Liu
2025	A*	`conf`	Balancing Two Classifiers via A Simplex ETF Structure for Model Calibration. CVPR Jiani Ni, He Zhao, Jintong Gao, Dandan Guo, Hongyuan Zha
2025	J	`jnl`	Balancing Two Classifiers via A Simplex ETF Structure for Model Calibration. CoRR Jiani Ni, He Zhao, Jintong Gao, Dandan Guo, Hongyuan Zha
2025	A*	`conf`	Beyond Words: Augmenting Discriminative Richness via Diffusions in Unsupervised Prompt Learning. CVPR Hairui Ren, Fan Tang, He Zhao, Zixuan Wang, Dandan Guo, Yi Chang
2025	J	`jnl`	Beyond Words: Augmenting Discriminative Richness via Diffusions in Unsupervised Prompt Learning. CoRR Hairui Ren, Fan Tang, He Zhao, Zixuan Wang, Dandan Guo, Yi Chang
2025	A*	`conf`	DRL: Decomposed Representation Learning for Tabular Anomaly Detection. ICLR Hangting Ye, He Zhao, Wei Fan, Mingyuan Zhou, Dandan Guo, Yi Chang
2025	J	`jnl`	Deep Neural Network Calibration by Reducing Classifier Shift with Stochastic Masking. CoRR Jiani Ni, He Zhao, Yibo Yang, Dandan Guo
2025	J	`jnl`	Direct Advantage Regression: Aligning LLMs with Online AI Reward. CoRR Li He, He Zhao, Stephen Wan, Dadong Wang, Lina Yao, Tongliang Liu
2025	J	`jnl`	Diverse Condensed Data Generation via Class Preserving Distribution Matching. Trans. Mach. Learn. Res. Dandan Guo, Zhuo Li, He Zhao, Mingyuan Zhou, Hongyuan Zha
2025	A*	`conf`	FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors. CVPR Changlong Shi, He Zhao, Bingjie Zhang, Mingyuan Zhou, Dandan Guo, Yi Chang
2025	J	`jnl`	FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors. CoRR Changlong Shi, He Zhao, Bingjie Zhang, Mingyuan Zhou, Dandan Guo, Yi Chang
2025	A*	`conf`	FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking. ICLR Changlong Shi, Jinmeng Li, He Zhao, Dandan Guo, Yi Chang
2025	J	`jnl`	FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking. CoRR Changlong Shi, Jinmeng Li, He Zhao, Dandan Guo, Yi Chang
2025	J	`jnl`	LLM Empowered Prototype Learning for Zero and Few-Shot Tasks on Tabular Data. CoRR Peng Wang, Dongsheng Wang, He Zhao, Hangting Ye, Dandan Guo, Yi Chang
2025	J	`jnl`	LLM Meeting Decision Trees on Tabular Data. CoRR Hangting Ye, Jinmeng Li, He Zhao, Dandan Guo, Yi Chang
2025	J	`jnl`	LLM Reading Tea Leaves: Automatically Evaluating Topic Models with Large Language Models. Trans. Assoc. Comput. Linguistics Xiaohao Yang, He Zhao, Dinh Q. Phung, Wray L. Buntine, Lan Du
2025	J	`jnl`	LLM as an Algorithmist: Enhancing Anomaly Detectors via Programmatic Synthesis. CoRR Hangting Ye, Jinmeng Li, He Zhao, Mingchen Zhuge, Dandan Guo, Yi Chang, Hongyuan Zha
2025	J	`jnl`	Merging Smarter, Generalizing Better: Enhancing Model Merging on OOD Data. CoRR Bingjie Zhang, Hongkang Li, Changlong Shi, Guowei Rong, He Zhao, Dongsheng Wang, Dandan Guo, Meng Wang
2025	J	`jnl`	Modality-Consistent Prompt Tuning With Optimal Transport. IEEE Trans. Circuits Syst. Video Technol. Hairui Ren, Fan Tang, Huangjie Zheng, He Zhao, Dandan Guo, Yi Chang
2025	—	`conf`	Neural Topic Modeling with Large Language Models in the Loop. ACL (1) Xiaohao Yang, He Zhao, Weijie Xu, Yuanyuan Qi, Jueqing Lu, Dinh Phung, Lan Du
2025	J	`jnl`	Prototype-Oriented Clean Subset Extraction for Noisy Long-Tailed Classification. IEEE Trans. Circuits Syst. Video Technol. Zhuo Li, He Zhao, Anningzhe Gao, Dandan Guo, Tsung-Hui Chang, Xiang Wan
2025	A*	`conf`	Rényi Neural Processes. ICML Xuesong Wang, He Zhao, Edwin V. Bonilla
2025	J	`jnl`	Synthesizing Minority Samples for Long-tailed Classification via Distribution Matching. Trans. Mach. Learn. Res. Zhuo Li, He Zhao, Jinke Ren, Anningzhe Gao, Dandan Guo, Xiang Wan, Hongyuan Zha
2024	J	`jnl`	A Class-aware Optimal Transport Approach with Higher-Order Moment Matching for Unsupervised Domain Adaptation. CoRR Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Q. Phung
2024	J	`jnl`	Bayesian Factorised Granger-Causal Graphs For Multivariate Time-series Data. CoRR He Zhao, Edwin V. Bonilla
2024	A*	`conf`	Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification. ICML Jintong Gao, He Zhao, Dandan Guo, Hongyuan Zha
2024	J	`jnl`	Enhancing Near OOD Detection in Prompt Learning: Maximum Gains, Minimal Costs. CoRR Myong Chol Jung, He Zhao, Joanna Dipnall, Belinda Gabbe, Lan Du
2024	J	`jnl`	Extracting Clean and Balanced Subset for Noisy Long-tailed Classification. CoRR Zhuo Li, He Zhao, Zhen Li, Tongliang Liu, Dandan Guo, Xiang Wan
2024	J	`jnl`	LLM Reading Tea Leaves: Automatically Evaluating Topic Models with Large Language Models. CoRR Xiaohao Yang, He Zhao, Dinh Q. Phung, Wray L. Buntine, Lan Du
2024	—	`conf`	Neural Topic Model with Distance Awareness. ICPR (9) Shangyu Chen, He Zhao, Viet H. Huynh, Dinh Q. Phung, Jianfei Cai
2024	J	`jnl`	Neural Topic Modeling with Large Language Models in the Loop. CoRR Xiaohao Yang, He Zhao, Weijie Xu, Yuanyuan Qi, Jueqing Lu, Dinh Q. Phung, Lan Du
2024	A*	`conf`	Optimal Transport for Structure Learning Under Missing Data. ICML Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Phung
2024	J	`jnl`	Optimal Transport for Structure Learning Under Missing Data. CoRR Vy Vo, He Zhao, Trung Le, Edwin V. Bonilla, Dinh Q. Phung
2024	A*	`conf`	PTaRL: Prototype-based Tabular Representation Learning via Space Calibration. ICLR Hangting Ye, Wei Fan, Xiaozhuang Song, Shun Zheng, He Zhao, Dandan Guo, Yi Chang
2024	J	`jnl`	PTaRL: Prototype-based Tabular Representation Learning via Space Calibration. CoRR Hangting Ye, Wei Fan, Xiaozhuang Song, Shun Zheng, He Zhao, Dandan Guo, Yi Chang
2024	A*	`conf`	Parameter Estimation in DAGs from Incomplete Data via Optimal Transport. ICML Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin V. Bonilla, Dinh Phung
2024	J	`jnl`	Rényi Neural Processes. CoRR Xuesong Wang, He Zhao, Edwin V. Bonilla
2024	J	`jnl`	Variational DAG Estimation via State Augmentation With Stochastic Permutations. CoRR Edwin V. Bonilla, Pantelis Elinas, He Zhao, Maurizio Filippone, Vassili Kitsios, Terry O'Kane
2023	A	`conf`	Adversarial local distribution regularization for knowledge distillation. WACV Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Phung
2023	A*	`conf`	Beyond Unimodal: Generalising Neural Processes for Multimodal Uncertainty Estimation. NeurIPS Myong Chol Jung, He Zhao, Joanna Dipnall, Lan Du
2023	J	`jnl`	Contrastively enforcing distinctiveness for multi-label image classification. Neurocomputing Son Duy Dao, He Zhao, Dinh Q. Phung, Jianfei Cai
2023	—	`conf`	Cross-Adversarial Local Distribution Regularization for Semi-supervised Medical Image Segmentation. MICCAI (1) Thanh Nguyen-Duc, Trung Le, Roland Bammer, He Zhao, Jianfei Cai, Dinh Q. Phung
2023	J	`jnl`	Cross-adversarial local distribution regularization for semi-supervised medical image segmentation. CoRR Thanh Nguyen-Duc, Trung Le, Roland Bammer, He Zhao, Jianfei Cai, Dinh Q. Phung
2023	A*	`conf`	Enhancing Minority Classes by Mixing: An Adaptative Optimal Transport Approach for Long-tailed Classification. NeurIPS Jintong Gao, He Zhao, Zhuo Li, Dandan Guo
2023	A*	`conf`	Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations. KDD Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin V. Bonilla, Gholamreza Haffari, Dinh Q. Phung
2023	J	`jnl`	Generating Adversarial Examples with Task Oriented Multi-Objective Optimization. CoRR Anh Tuan Bui, Trung Le, He Zhao, Quan Hung Tran, Paul Montague, Dinh Q. Phung
2023	J	`jnl`	Generating Adversarial Examples with Task Oriented Multi-Objective Optimization. Trans. Mach. Learn. Res. Anh Tuan Bui, Trung Le, He Zhao, Quan Hung Tran, Paul Montague, Dinh Phung
2023	J	`jnl`	Learning Directed Graphical Models with Optimal Transport. CoRR Vy Vo, Trung Le, Long Tung Vuong, He Zhao, Edwin V. Bonilla, Dinh Q. Phung
2023	J	`jnl`	Multimodal Neural Processes for Uncertainty Estimation. CoRR Myong Chol Jung, He Zhao, Joanna Dipnall, Belinda Gabbe, Lan Du
2023	A*	`conf`	NPCL: Neural Processes for Uncertainty-Aware Continual Learning. NeurIPS Saurav Jha, Dong Gong, He Zhao, Lina Yao
2023	J	`jnl`	NPCL: Neural Processes for Uncertainty-Aware Continual Learning. CoRR Saurav Jha, Dong Gong, He Zhao, Lina Yao
2023	A	`conf`	Open-Vocabulary Multi-label Image Classification with Pretrained Vision-Language Model. ICME Son Duy Dao, Dat Huynh, He Zhao, Dinh Phung, Jianfei Cai
2023	J	`jnl`	Towards Generalising Neural Topical Representations. CoRR Xiaohao Yang, He Zhao, Dinh Phung, Lan Du
2023	A*	`conf`	Transformed Distribution Matching for Missing Value Imputation. ICML He Zhao, Ke Sun, Amir Dezfouli, Edwin V. Bonilla
2023	J	`jnl`	Transformed Distribution Matching for Missing Value Imputation. CoRR He Zhao, Ke Sun, Amir Dezfouli, Edwin V. Bonilla
2023	A*	`conf`	Vector Quantized Wasserstein Auto-Encoder. ICML Long Tung Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung
2023	J	`jnl`	Vector Quantized Wasserstein Auto-Encoder. CoRR Tung-Long Vuong, Trung Le, He Zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Q. Phung
2022	—	`conf`	A Label-Aware Autoregressive Framework for Cross-Domain NER. NAACL-HLT (Findings) Jinpeng Hu, He Zhao, Dan Guo, Xiang Wan, Tsung-Hui Chang
2022	A*	`conf`	A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. ICLR Anh Tuan Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung
2022	J	`jnl`	A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. CoRR Tuan-Anh Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung
2022	A*	`conf`	Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport. NeurIPS Dandan Guo, Long Tian, He Zhao, Mingyuan Zhou, Hongyuan Zha
2022	J	`jnl`	Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport. CoRR Dandan Guo, Long Tian, He Zhao, Mingyuan Zhou, Hongyuan Zha
2022	A	`conf`	Cycle class consistency with distributional optimal transport and knowledge distillation for unsupervised domain adaptation. UAI Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Q. Phung
2022	J	`jnl`	Learning to Counter: Stochastic Feature-based Learning for Diverse Counterfactual Explanations. CoRR Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin V. Bonilla, Gholamreza Haffari, Dinh Q. Phung
2022	A*	`conf`	Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification. NeurIPS Dandan Guo, Zhuo Li, Meixi Zheng, He Zhao, Mingyuan Zhou, Hongyuan Zha
2022	J	`jnl`	Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification. CoRR Dandan Guo, Zhuo Li, Meixi Zheng, He Zhao, Mingyuan Zhou, Hongyuan Zha
2022	—	`conf`	MED-TEX: Transfer and Explain Knowledge with Less Data from Pretrained Medical Imaging Models. ISBI Thanh Nguyen-Duc, He Zhao, Jianfei Cai, Dinh Phung
2022	A	`conf`	On Global-view Based Defense via Adversarial Attack and Defense Risk Guaranteed Bounds. AISTATS Trung Le, Anh Tuan Bui, Le Minh Tri Tue, He Zhao, Paul Montague, Quan Hung Tran, Dinh Q. Phung
2022	A	`conf`	Particle-based Adversarial Local Distribution Regularization. AISTATS Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Q. Phung
2022	A*	`conf`	Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings. ICLR Dongsheng Wang, Dandan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen, Mingyuan Zhou
2022	J	`jnl`	Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings. CoRR Dongsheng Wang, Dandan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen, Mingyuan Zhou
2022	A*	`conf`	Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture. NeurIPS Myong Chol Jung, He Zhao, Joanna Dipnall, Belinda Gabbe, Lan Du
2022	J	`jnl`	Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture. CoRR Myong Chol Jung, He Zhao, Joanna Dipnall, Belinda Gabbe, Lan Du
2021	J	`jnl`	Improved and Efficient Text Adversarial Attacks using Target Information. CoRR Mahmoud Hossam, Trung Le, He Zhao, Viet Huynh, Dinh Phung
2021	A*	`conf`	Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness. AAAI Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung
2021	A	`conf`	Most: multi-source domain adaptation via optimal transport for student-teacher learning. UAI Tuan Nguyen, Trung Le, He Zhao, Quan Hung Tran, Truyen Nguyen, Dinh Q. Phung
2021	—	`conf`	Neural Attention-Aware Hierarchical Topic Model. EMNLP (1) Yuan Jin, He Zhao, Ming Liu, Lan Du, Wray L. Buntine
2021	J	`jnl`	Neural Attention-Aware Hierarchical Topic Model. CoRR Yuan Jin, He Zhao, Ming Liu, Lan Du, Wray L. Buntine
2021	A*	`conf`	Neural Topic Model via Optimal Transport. ICLR He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L. Buntine
2021	A*	`conf`	Optimal Transport for Deep Generative Models: State of the Art and Research Challenges. IJCAI Viet Huynh, Dinh Q. Phung, He Zhao
2021	A*	`conf`	Topic Modelling Meets Deep Neural Networks: A Survey. IJCAI He Zhao, Dinh Q. Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine
2021	J	`jnl`	Topic Modelling Meets Deep Neural Networks: A Survey. CoRR He Zhao, Dinh Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine
2021	J	`jnl`	Understanding and Achieving Efficient Robustness with Adversarial Contrastive Learning. CoRR Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Seyit Camtepe, Dinh Phung
2020	B	`conf`	Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability. ICPR Mahmoud Hossam, Trung Le, He Zhao, Dinh Phung
2020	J	`jnl`	Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability. CoRR Mahmoud Hossam, Trung Le, He Zhao, Dinh Phung
2020	—	`conf`	Improving Adversarial Robustness by Enforcing Local and Global Compactness. ECCV (27) Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. DeVel, Tamas Abraham, Dinh Q. Phung
2020	J	`jnl`	Improving Adversarial Robustness by Enforcing Local and Global Compactness. CoRR Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. DeVel, Tamas Abraham, Dinh Phung
2020	J	`jnl`	Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness. CoRR Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. DeVel, Tamas Abraham, Dinh Phung
2020	J	`jnl`	Leveraging Cross Feedback of User and Item Embeddings for Variational Autoencoder based Collaborative Filtering. CoRR Yuan Jin, He Zhao, Ming Liu, Lan Du, Yunfeng Li, Ruohua Xu, Longxiang Gao
2020	J	`jnl`	MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models. CoRR Thanh Nguyen-Duc, He Zhao, Jianfei Cai, Dinh Phung
2020	J	`jnl`	Neural Sinkhorn Topic Model. CoRR He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray L. Buntine
2020	A*	`conf`	OTLDA: A Geometry-aware Optimal Transport Approach for Topic Modeling. NeurIPS Viet Huynh, He Zhao, Dinh Phung
2020	A*	`conf`	SummPip: Unsupervised Multi-Document Summarization with Sentence Graph Compression. SIGIR Jinming Zhao, Ming Liu, Longxiang Gao, Yuan Jin, Lan Du, He Zhao, He Zhang, Gholamreza Haffari
2020	J	`jnl`	SummPip: Unsupervised Multi-Document Summarization with Sentence Graph Compression. CoRR Jinming Zhao, Ming Liu, Longxiang Gao, Yuan Jin, Lan Du, He Zhao, He Zhang, Gholamreza Haffari
2020	J	`jnl`	Towards Understanding Pixel Vulnerability under Adversarial Attacks for Images. CoRR He Zhao, Trung Le, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung
2020	A	`conf`	Variational Autoencoders for Sparse and Overdispersed Discrete Data. AISTATS He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Dinh Phung, Mingyuan Zhou
2019	—	`conf`	Leveraging Meta Information in Short Text Aggregation. ACL (1) He Zhao, Lan Du, Guanfeng Liu, Wray L. Buntine
2019	J	`jnl`	Leveraging external information in topic modelling. Knowl. Inf. Syst. He Zhao, Lan Du, Wray L. Buntine, Gang Liu
2019	J	`jnl`	Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions. CoRR He Zhao, Trung Le, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung
2019	—	`—`	Structured Bayesian Latent Factor Models with Meta-data. He Zhao
2019	J	`jnl`	Variational Autoencoders for Sparse and Overdispersed Discrete Data. CoRR He Zhao, Piyush Rai, Lan Du, Wray L. Buntine, Mingyuan Zhou
2018	A	`conf`	Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences. AISTATS He Zhao, Piyush Rai, Lan Du, Wray L. Buntine
2018	A*	`conf`	Dirichlet belief networks for topic structure learning. NeurIPS He Zhao, Lan Du, Wray L. Buntine, Mingyuan Zhou
2018	J	`jnl`	Dirichlet belief networks for topic structure learning. CoRR He Zhao, Lan Du, Wray L. Buntine, Mingyuan Zhou
2018	A*	`conf`	Inter and Intra Topic Structure Learning with Word Embeddings. ICML He Zhao, Lan Du, Wray L. Buntine, Mingyuan Zhou
2017	C	`conf`	A Word Embeddings Informed Focused Topic Model. ACML He Zhao, Lan Du, Wray L. Buntine
2017	A*	`conf`	Leveraging Node Attributes for Incomplete Relational Data. ICML He Zhao, Lan Du, Wray L. Buntine
2017	J	`jnl`	Leveraging Node Attributes for Incomplete Relational Data. CoRR He Zhao, Lan Du, Wray L. Buntine
2017	A*	`conf`	MetaLDA: A Topic Model that Efficiently Incorporates Meta Information. ICDM He Zhao, Lan Du, Wray L. Buntine, Gang Liu
2017	J	`jnl`	MetaLDA: a Topic Model that Efficiently Incorporates Meta information. CoRR He Zhao, Lan Du, Wray L. Buntine, Gang Liu