Chao Zhang

ORCID

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 139

Top Venues

Publications

Yue Yu, Jiaming Shen, Tianqi Liu, Zhen Qin, Jing Nathan Yan, Jialu Liu, Chao Zhang, Michael Bendersky
Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning. ACL (1) (2024)
Haoxin Liu, Shangqing Xu, Zhiyuan Zhao, Lingkai Kong, Harshavardhan Kamarthi, Aditya B. Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang, B. Aditya Prakash
Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis. CoRR (2024)
Rongzhi Zhang, Jiaming Shen, Tianqi Liu, Haorui Wang, Zhen Qin, Feng Han, Jialu Liu, Simon Baumgartner, Michael Bendersky, Chao Zhang
PLaD: Preference-based Large Language Model Distillation with Pseudo-Preference Pairs. CoRR (2024)
Yuzhao Heng, Chunyuan Deng, Yitong Li, Yue Yu, Yinghao Li, Rongzhi Zhang, Chao Zhang
ProgGen: Generating Named Entity Recognition Datasets Step-by-step with Self-Reflexive Large Language Models. CoRR (2024)
Lingkai Kong, Haotian Sun, Yuchen Zhuang, Haorui Wang, Wenhao Mu, Chao Zhang
Two Birds with One Stone: Enhancing Uncertainty Quantification and Interpretability with Graph Functional Neural Process. AISTATS (2024)
Vidit Jain, Mukund Rungta, Yuchen Zhuang, Yue Yu, Zeyu Wang, Mu Gao, Jeffrey Skolnick, Chao Zhang
HiGen: Hierarchy-Aware Sequence Generation for Hierarchical Text Classification. EACL (1) (2024)
Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang, B. Aditya Prakash
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning. CoRR (2024)
Rongzhi Zhang, Jiaming Shen, Tianqi Liu, Haorui Wang, Zhen Qin, Feng Han, Jialu Liu, Simon Baumgartner, Michael Bendersky, Chao Zhang
PLaD: Preference-based Large Language Model Distillation with Pseudo-Preference Pairs. ACL (Findings) (2024)
Yuchen Zhuang, Xiang Chen, Tong Yu, Saayan Mitra, Victor Bursztyn, Ryan A. Rossi, Somdeb Sarkhel, Chao Zhang
ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search. ICLR (2024)
Lingkai Kong, Haorui Wang, Wenhao Mu, Yuanqi Du, Yuchen Zhuang, Yifei Zhou, Yue Song, Rongzhi Zhang, Kai Wang, Chao Zhang
Aligning Large Language Models with Representation Editing: A Control Perspective. CoRR (2024)
Lingxi Zhang, Yue Yu, Kuan Wang, Chao Zhang
ARL2: Aligning Retrievers for Black-box Large Language Models via Self-guided Adaptive Relevance Labeling. CoRR (2024)
Lingkai Kong, Yuanqi Du, Wenhao Mu, Kirill Neklyudov, Valentin De Bortol, Haorui Wang, Dongxia Wu, Aaron Ferber, Yi-An Ma, Carla P. Gomes, Chao Zhang
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints. CoRR (2024)
Ran Xu, Wenqi Shi, Yue Yu, Yuchen Zhuang, Yanqiao Zhu, May D. Wang, Joyce C. Ho, Chao Zhang, Carl Yang
BMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers. CoRR (2024)
Haorui Wang, Marta Skreta, Cher-Tian Ser, Wenhao Gao, Lingkai Kong, Felix Streith-Kalthoff, Chenru Duan, Yuchen Zhuang, Yue Yu, Yanqiao Zhu, Yuanqi Du, Alán Aspuru-Guzik, Kirill Neklyudov, Chao Zhang
Efficient Evolutionary Search Over Chemical Space with Large Language Models. CoRR (2024)
Jiahang Tu, Wei Ji, Hanbin Zhao, Chao Zhang, Roger Zimmermann, Hui Qian
DriveDiTFit: Fine-tuning Diffusion Transformers for Autonomous Driving. CoRR (2024)
Yuchen Zhuang, Haotian Sun, Yue Yu, Rushi Qiang, Qifan Wang, Chao Zhang, Bo Dai
HYDRA: Model Factorization Framework for Black-Box LLM Personalization. CoRR (2024)
Rongzhi Zhang, Jiaming Shen, Tianqi Liu, Jialu Liu, Michael Bendersky, Marc Najork, Chao Zhang
Knowledge Distillation with Perturbed Loss: From a Vanilla Teacher to a Proxy Teacher. KDD (2024)
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
Learning Graph Structures and Uncertainty for Accurate and Calibrated Time-series Forecasting. CoRR (2024)
Yinghao Li, Lingkai Kong, Yuanqi Du, Yue Yu, Yuchen Zhuang, Wenhao Mu, Chao Zhang
MUBen: Benchmarking the Uncertainty of Molecular Representation Models. Trans. Mach. Learn. Res. 2024 (2024)
Haotian Sun, Yuchen Zhuang, Wei Wei, Chao Zhang, Bo Dai
BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models. CoRR (2024)
Yuchen Zhuang, Xin Shen, Yan Zhao, Chaosheng Dong, Ming Wang, Jin Li, Chao Zhang
G-STO: Sequential Main Shopping Intention Detection via Graph-Regularized Stochastic Transformer. CoRR (2023)
Yinghao Li, Colin Lockard, Prashant Shiralkar, Chao Zhang
Extracting Shopping Interest-Related Product Types from the Web. ACL (Findings) (2023)
Yuchen Zhuang, Xin Shen, Yan Zhao, Chaosheng Dong, Ming Wang, Jin Li, Chao Zhang
G-STO: Sequential Main Shopping Intention Detection via Graph-Regularized Stochastic Transformer. CIKM (2023)
Yang Liu, Xiang Ao, Linfeng Dong, Chao Zhang, Jin Wang, Qing He
Spatiotemporal Activity Modeling via Hierarchical Cross-Modal Embedding : Extended Abstract. ICDE (2023)
Yuchen Zhuang, Yue Yu, Kuan Wang, Haotian Sun, Chao Zhang
ToolQA: A Dataset for LLM Question Answering with External Tools. CoRR (2023)
Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang
DF2: Distribution-Free Decision-Focused Learning. CoRR (2023)
Yue Yu, Yuchen Zhuang, Jieyu Zhang, Yu Meng, Alexander Ratner, Ranjay Krishna, Jiaming Shen, Chao Zhang
Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias. CoRR (2023)
Yuchen Zhuang, Yue Yu, Lingkai Kong, Xiang Chen, Chao Zhang
DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling. KDD (2023)
Ran Xu, Yue Yu, Hejie Cui, Xuan Kan, Yanqiao Zhu, Joyce C. Ho, Chao Zhang, Carl Yang
Neighborhood-Regularized Self-Training for Learning with Few Labels. AAAI (2023)
Yue Yu, Yuchen Zhuang, Rongzhi Zhang, Yu Meng, Jiaming Shen, Chao Zhang
ReGen: Zero-Shot Text Classification via Training Data Generation with Progressive Dense Retrieval. ACL (Findings) (2023)
Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang, B. Aditya Prakash, Chao Zhang
Autoregressive Diffusion Model for Graph Generation. CoRR (2023)
Lingkai Kong, Harshavardhan Kamarthi, Peng Chen, B. Aditya Prakash, Chao Zhang
Uncertainty Quantification in Deep Learning. KDD (2023)
Rongzhi Zhang, Yue Yu, Jiaming Shen, Xiquan Cui, Chao Zhang
Local Boosting for Weakly-Supervised Learning. KDD (2023)
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting. KDD (2023)
Yue Yu, Rongzhi Zhang, Ran Xu, Jieyu Zhang, Jiaming Shen, Chao Zhang
Cold-Start Data Selection for Better Few-shot Language Model Fine-tuning: A Prompt-based Uncertainty Propagation Approach. ACL (1) (2023)
Chen Luo, Rahul Goutam, Haiyang Zhang, Chao Zhang, Yangqiu Song, Bing Yin
Implicit Query Parsing at Amazon Product Search. SIGIR (2023)
Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang, B. Aditya Prakash, Chao Zhang
Autoregressive Diffusion Model for Graph Generation. ICML (2023)
Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang
Deep Dag Learning of Effective Brain Connectivity for FMRI Analysis. ISBI (2023)
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting. WWW (2022)
Yue Yu, Chenyan Xiong, Si Sun, Chao Zhang, Arnold Overwijk
COCO-DR: Combating Distribution Shifts in Zero-Shot Dense Retrieval with Contrastive and Distributionally Robust Learning. CoRR (2022)
Di Yao, Gao Cong, Chao Zhang, Xuying Meng, Rongchang Duan, Jingping Bi
A Linear Time Approach to Computing Time Series Similarity Based on Deep Metric Learning. IEEE Trans. Knowl. Data Eng. 34 (10) (2022)
Qi Zhu, Chao Zhang, Chanyoung Park, Carl Yang, Jiawei Han
Shift-Robust Node Classification via Graph Adversarial Clustering. CoRR (2022)
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting. CoRR (2021)
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting. CoRR (2021)
Hongzhi Shi, Yong Li, Hancheng Cao, Xiangxin Zhou, Chao Zhang, Vassilis Kostakos
Semantics-Aware Hidden Markov Model for Human Mobility. IEEE Trans. Knowl. Data Eng. 33 (3) (2021)
Yue Yu, Simiao Zuo, Haoming Jiang, Wendi Ren, Tuo Zhao, Chao Zhang
Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach. NAACL-HLT (2021)
Simiao Zuo, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang, Tuo Zhao, Hongyuan Zha
Self-Training with Differentiable Teacher. CoRR (2021)
Qi Zhu, Carl Yang, Yidan Xu, Haonan Wang, Chao Zhang, Jiawei Han
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization. NeurIPS (2021)
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting. NeurIPS (2021)
Yue Yu, Kexin Huang, Chao Zhang, Lucas M. Glass, Jimeng Sun, Cao Xiao
SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization. Bioinform. 37 (18) (2021)
Wei Zeng, Xiaozhe Ren, Teng Su, Hui Wang, Yi Liao, Zhiwei Wang, Xin Jiang, ZhenZhang Yang, Kaisheng Wang, Xiaoda Zhang, Chen Li, Ziyan Gong, Yifan Yao, Xinjing Huang, Jun Wang, Jianfeng Yu, Qi Guo, Yue Yu, Yan Zhang, Jin Wang, Hengtao Tao, Dasen Yan, Zexuan Yi, Fang Peng, Fangqing Jiang, Han Zhang, Lingfeng Deng, Yehong Zhang, Zhe Lin, Chao Zhang, Shaojie Zhang, Mingyue Guo, Shanzhi Gu, Gaojun Fan, Yaowei Wang, Xuefeng Jin, Qun Liu, Yonghong Tian
PanGu-α: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation. CoRR (2021)
Kejing Yin, Ardavan Afshar, Joyce C. Ho, William K. Cheung, Chao Zhang, Jimeng Sun
LogPar: Logistic PARAFAC2 Factorization for Temporal Binary Data with Missing Values. KDD (2020)
Yu Meng, Yunyi Zhang, Jiaxin Huang, Yu Zhang, Chao Zhang, Jiawei Han
Hierarchical Topic Mining via Joint Spherical Tree and Text Embedding. KDD (2020)
Yu Meng, Yunyi Zhang, Jiaxin Huang, Chenyan Xiong, Heng Ji, Chao Zhang, Jiawei Han
Text Classification Using Label Names Only: A Language Model Self-Training Approach. CoRR (2020)
Lingkai Kong, Haoming Jiang, Yuchen Zhuang, Jie Lyu, Tuo Zhao, Chao Zhang
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data. EMNLP (1) (2020)
Wanzheng Zhu, Hongyu Gong, Jiaming Shen, Chao Zhang, Jingbo Shang, Suma Bhat, Jiawei Han
FUSE: Multi-faceted Set Expansion by Coherent Clustering of Skip-Grams. ECML/PKDD (3) (2020)
Honglei Zhuang, Fang Guo, Chao Zhang, Liyuan Liu, Jiawei Han
Joint Aspect-Sentiment Analysis with Minimal User Guidance. SIGIR (2020)
Wanzheng Zhu, Chao Zhang, Shuochao Yao, Xiaobin Gao, Jiawei Han
A Spherical Hidden Markov Model for Semantics-Rich Human Mobility Modeling. CoRR (2020)
Yu Meng, Jiaxin Huang, Guangyuan Wang, Zihan Wang, Chao Zhang, Jiawei Han
Unsupervised Word Embedding Learning by Incorporating Local and Global Contexts. Frontiers Big Data 3 (2020)
Shi Zhi, Liyuan Liu, Yu Zhang, Shiyin Wang, Qi Li, Chao Zhang, Jiawei Han
Partially-Typed NER Datasets Integration: Connecting Practice to Theory. CoRR (2020)
Huajie Shao, Dachun Sun, Jiahao Wu, Zecheng Zhang, Aston Zhang, Shuochao Yao, Shengzhong Liu, Tianshi Wang, Chao Zhang, Tarek F. Abdelzaher
paper2repo: GitHub Repository Recommendation for Academic Papers. WWW (2020)
Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, Chao Zhang
BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. CoRR (2020)
Yu Meng, Yunyi Zhang, Jiaxin Huang, Chenyan Xiong, Heng Ji, Chao Zhang, Jiawei Han
Text Classification Using Label Names Only: A Language Model Self-Training Approach. EMNLP (1) (2020)
Wendi Ren, Yinghao Li, Hanting Su, David Kartchner, Cassie Mitchell, Chao Zhang
Denoising Multi-Source Weak Supervision for Neural Text Classification. CoRR (2020)
Lingkai Kong, Haoming Jiang, Yuchen Zhuang, Jie Lyu, Tuo Zhao, Chao Zhang
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data. CoRR (2020)
Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, Chao Zhang
BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. KDD (2020)
Lingkai Kong, Jimeng Sun, Chao Zhang
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates. ICML (2020)
Yu Meng, Yunyi Zhang, Jiaxin Huang, Yu Zhang, Chao Zhang, Jiawei Han
Hierarchical Topic Mining via Joint Spherical Tree and Text Embedding. CoRR (2020)
Qi Zhu, Yidan Xu, Haonan Wang, Chao Zhang, Jiawei Han, Carl Yang
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization. CoRR (2020)
Rongzhi Zhang, Yue Yu, Chao Zhang
SeqMix: Augmenting Active Sequence Labeling via Sequence Mixup. CoRR (2020)
Carl Yang, Liyuan Liu, Mengxiong Liu, Zongyi Wang, Chao Zhang, Jiawei Han
Graph Clustering with Embedding Propagation. IEEE BigData (2020)
Yue Yu, Yinghao Li, Jiaming Shen, Hao Feng, Jimeng Sun, Chao Zhang
STEAM: Self-Supervised Taxonomy Expansion with Mini-Paths. KDD (2020)
Yue Yu, Yinghao Li, Jiaming Shen, Hao Feng, Jimeng Sun, Chao Zhang
STEAM: Self-Supervised Taxonomy Expansion with Mini-Paths. CoRR (2020)
Yue Yu, Simiao Zuo, Haoming Jiang, Wendi Ren, Tuo Zhao, Chao Zhang
Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach. CoRR (2020)
Lingkai Kong, Jimeng Sun, Chao Zhang
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates. CoRR (2020)
Wendi Ren, Yinghao Li, Hanting Su, David Kartchner, Cassie Mitchell, Chao Zhang
Denoising Multi-Source Weak Supervision for Neural Text Classification. EMNLP (Findings) (2020)
Rongzhi Zhang, Yue Yu, Chao Zhang
SeqMix: Augmenting Active Sequence Labeling via Sequence Mixup. EMNLP (1) (2020)
Yu Meng, Jiaxin Huang, Guangyuan Wang, Zihan Wang, Chao Zhang, Yu Zhang, Jiawei Han
Discriminative Topic Mining via Category-Name Guided Text Embedding. WWW (2020)
Huajie Shao, Dachun Sun, Jiahao Wu, Zecheng Zhang, Aston Zhang, Shuochao Yao, Shengzhong Liu, Tianshi Wang, Chao Zhang, Tarek F. Abdelzaher
paper2repo: GitHub Repository Recommendation for Academic Papers. CoRR (2020)
Yue Yu, Kexin Huang, Chao Zhang, Lucas M. Glass, Jimeng Sun, Cao Xiao
SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization. CoRR (2020)
Yucheng Chen, Matus Telgarsky, Chao Zhang, Bolton Bailey, Daniel Hsu, Jian Peng
A gradual, semi-discrete approach to generative network training via explicit Wasserstein minimization. CoRR (2019)
Di Yao, Gao Cong, Chao Zhang, Jingping Bi
Computing Trajectory Similarity in Linear Time: A Generic Seed-Guided Neural Metric Learning Approach. ICDE (2019)
Yucheng Chen, Matus Telgarsky, Chao Zhang, Bolton Bailey, Daniel Hsu, Jian Peng
A Gradual, Semi-Discrete Approach to Generative Network Training via Explicit Wasserstein Minimization. ICML (2019)
Yu Meng, Jiaming Shen, Chao Zhang, Jiawei Han
Weakly-Supervised Hierarchical Text Classification. AAAI (2019)
Jie Feng, Mingyang Zhang, Huandong Wang, Zeyu Yang, Chao Zhang, Yong Li, Depeng Jin
DPLink: User Identity Linkage via Deep Neural Network From Heterogeneous Mobility Data. WWW (2019)
Carl Yang, Dai Teng, Siyang Liu, Sayantani Basu, Jieyu Zhang, Jiaming Shen, Chao Zhang, Jingbo Shang, Lance M. Kaplan, Timothy Harratty, Jiawei Han
CubeNet: Multi-Facet Hierarchical Heterogeneous Network Construction, Analysis, and Mining. CoRR (2019)
Sha Li, Chao Zhang, Dongming Lei, Ji Li, Jiawei Han
GeoAttn: Localization of Social Media Messages via Attentional Memory Network. SDM (2019)
Yu Meng, Jiaxin Huang, Guangyuan Wang, Chao Zhang, Honglei Zhuang, Lance M. Kaplan, Jiawei Han
Spherical Text Embedding. CoRR (2019)
Jiaming Shen, Zeqiu Wu, Dongming Lei, Chao Zhang, Xiang Ren, Michelle T. Vanni, Brian M. Sadler, Jiawei Han
HiExpan: Task-Guided Taxonomy Construction by Hierarchical Tree Expansion. CoRR (2019)
Hongzhi Shi, Hancheng Cao, Xiangxin Zhou, Yong Li, Chao Zhang, Vassilis Kostakos, Funing Sun, Fanchao Meng
Semantics-Aware Hidden Markov Model for Human Mobility. SDM (2019)
Yu Meng, Jiaxin Huang, Guangyuan Wang, Zihan Wang, Chao Zhang, Jiawei Han
CatE: Category-Name GuidedWord Embedding. CoRR (2019)
Wanzheng Zhu, Hongyu Gong, Jiaming Shen, Chao Zhang, Jingbo Shang, Suma Bhat, Jiawei Han
FUSE: Multi-Faceted Set Expansion by Coherent Clustering of Skip-grams. CoRR (2019)
Hongzhi Shi, Chao Zhang, Quanming Yao, Yong Li, Funing Sun, Depeng Jin
State-Sharing Sparse Hidden Markov Models for Personalized Sequences. KDD (2019)
Yu Meng, Jiaxin Huang, Guangyuan Wang, Chao Zhang, Honglei Zhuang, Lance M. Kaplan, Jiawei Han
Spherical Text Embedding. NeurIPS (2019)
Chao Zhang, Fangbo Tao, Xiusi Chen, Jiaming Shen, Meng Jiang, Brian M. Sadler, Michelle Vanni, Jiawei Han
TaxoGen: Unsupervised Topic Taxonomy Construction by Adaptive Term Embedding and Clustering. CoRR (2018)
Chao Zhang, Fangbo Tao, Xiusi Chen, Jiaming Shen, Meng Jiang, Brian M. Sadler, Michelle Vanni, Jiawei Han
TaxoGen: Unsupervised Topic Taxonomy Construction by Adaptive Term Embedding and Clustering. KDD (2018)
Jie Feng, Yong Li, Chao Zhang, Funing Sun, Fanchao Meng, Ang Guo, Depeng Jin
DeepMove: Predicting Human Mobility with Attentional Recurrent Networks. WWW (2018)
Zhenguang Liu, Yingjie Xia, Qi Liu, Qinming He, Chao Zhang, Roger Zimmermann
Toward Personalized Activity Level Prediction in Community Question Answering Websites. ACM Trans. Multim. Comput. Commun. Appl. 14 (2s) (2018)
Shuochao Yao, Yiran Zhao, Aston Zhang, Shaohan Hu, Huajie Shao, Chao Zhang, Lu Su, Tarek F. Abdelzaher
Deep Learning for the Internet of Things. Computer 51 (5) (2018)
Yu Shi, Qi Zhu, Fang Guo, Chao Zhang, Jiawei Han
Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks. CoRR (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Chao Zhang