Efficient similarity matching of Time Series Cliques with natural relations. - Zhe Zhao 001; Bin Cui 001; Wee Hyong Tok; Jiakui Zhao (ICDE, 2010)

Multiple feature fusion for social media applications. - Bin Cui 001; Anthony K. H. Tung; Ce Zhang 001; Zhe Zhao 001 (SIGMOD Conference, 2010)

Recommending Flickr groups with social topic model. - Jingdong Wang 001; Zhe Zhao 001; Jiazhen Zhou; Hao Wang 005; Bin Cui 001; Guojun Qi (Inf. Retr., 2012)

Extracting representative motion flows for effective video retrieval. - Zhe Zhao 001; Bin Cui 001; Gao Cong; Zi Huang; Heng Tao Shen (Multim. Tools Appl., 2012)

A Framework for Similarity Search of Time Series Cliques with Natural Relations. - Bin Cui 001; Zhe Zhao 001; Wee Hyong Tok (IEEE Trans. Knowl. Data Eng., 2012)

Questions about questions: an empirical analysis of information needs on Twitter. - Zhe Zhao 001; Qiaozhu Mei (WWW, 2013)

Predicting bursts and popularity of hashtags in real-time. - Shoubin Kong; Qiaozhu Mei; Ling Feng; Fei Ye; Zhe Zhao 001 (SIGIR, 2014)

Real-Time Predicting Bursting Hashtags on Twitter. - Shoubin Kong; Qiaozhu Mei; Ling Feng; Zhe Zhao 001 (WAIM, 2014)

On the Real-time Prediction Problems of Bursting Hashtags in Twitter. - Shoubin Kong; Qiaozhu Mei; Ling Feng; Zhe Zhao 001; Fei Ye (CoRR, 2014)

Improving User Topic Interest Profiles by Behavior Factorization. - Zhe Zhao 001; Zhiyuan Cheng 002; Lichan Hong; Ed Huai-hsin Chi (WWW, 2015)

Enquiring Minds: Early Detection of Rumors in Social Media from Enquiry Posts. - Zhe Zhao 001; Paul Resnick; Qiaozhu Mei (WWW, 2015)

Towards the prediction problems of bursting hashtags on Twitter. - Shoubin Kong; Fei Ye; Ling Feng; Zhe Zhao 001 (J. Assoc. Inf. Sci. Technol., 2015)

Detecting Social Media Icebergs by Their Tips: Rumors, Persuasion Campaigns, and Information Needs. - Zhe Zhao 001 (WSDM, 2016)

Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations. - Alex Beutel; Jilin Chen; Zhe Zhao 001; Ed H. Chi (CoRR, 2017)

Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts. - Jiaqi Ma 001; Zhe Zhao 001; Xinyang Yi; Jilin Chen; Lichan Hong; Ed H. Chi (KDD, 2018)

Identify Shifts of Word Semantics through Bayesian Surprise. - Zhuofeng Wu 001; Cheng Li 012; Zhe Zhao 001; Fei Wu 001; Qiaozhu Mei (SIGIR, 2018)

SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning. - Jiaqi Ma 001; Zhe Zhao 001; Jilin Chen; Ang Li; Lichan Hong; Ed H. Chi (AAAI, 2019)

Fairness in Recommendation Ranking through Pairwise Comparisons. - Alex Beutel; Jilin Chen; Tulsee Doshi; Hai Qian; Li Wei; Yi Wu; Lukasz Heldt; Zhe Zhao 001; Lichan Hong; Ed H. Chi; Cristos Goodrow (KDD, 2019)

Sampling-bias-corrected neural modeling for large corpus item recommendations. - Xinyang Yi; Ji Yang; Lichan Hong; Derek Zhiyuan Cheng; Lukasz Heldt; Aditee Kumthekar; Zhe Zhao 001; Li Wei; Ed H. Chi (RecSys, 2019)

Recommending what video to watch next: a multitask ranking system. - Zhe Zhao 001; Lichan Hong; Li Wei; Jilin Chen; Aniruddh Nath; Shawn Andrews; Aditee Kumthekar; Maheswaran Sathiamoorthy; Xinyang Yi; Ed H. Chi (RecSys, 2019)

Multitask Mixture of Sequential Experts for User Activity Streams. - Zhen Qin 001; Yicheng Cheng; Zhe Zhao 001; Zhe Chen; Donald Metzler; Jingzheng Qin (KDD, 2020)

Off-policy Learning in Two-stage Recommender Systems. - Jiaqi Ma 001; Zhe Zhao 001; Xinyang Yi; Ji Yang; Minmin Chen; Jiaxi Tang; Lichan Hong; Ed H. Chi (WWW, 2020)

Understanding and Improving Knowledge Distillation. - Jiaxi Tang; Rakesh Shivanna; Zhe Zhao 001; Dong Lin; Anima Singh; Ed H. Chi; Sagar Jain (CoRR, 2020)

HyperGrid: Efficient Multi-Task Transformers with Grid-wise Decomposable Hyper Projections. - Yi Tay; Zhe Zhao 001; Dara Bahri; Donald Metzler; Da-Cheng Juan (CoRR, 2020)

Small Towers Make Big Differences. - Yuyan Wang; Zhe Zhao 001; Bo Dai 001; Christopher Fifty; Dong Lin; Lichan Hong; Ed H. Chi (CoRR, 2020)

Measuring and Harnessing Transference in Multi-Task Learning. - Christopher Fifty; Ehsan Amid; Zhe Zhao 001; Tianhe Yu; Rohan Anil; Chelsea Finn (CoRR, 2020)

Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. - Jiaqi Ma 001; Xinyang Yi; Weijing Tang; Zhe Zhao 001; Lichan Hong; Ed H. Chi; Qiaozhu Mei (AISTATS, 2021)

HyperGrid Transformers: Towards A Single Model for Multiple Tasks. - Yi Tay; Zhe Zhao 001; Dara Bahri; Donald Metzler; Da-Cheng Juan (ICLR, 2021)

Synthesizer: Rethinking Self-Attention for Transformer Models. - Yi Tay; Dara Bahri; Donald Metzler; Da-Cheng Juan; Zhe Zhao 001; Che Zheng (ICML, 2021)

Efficiently Identifying Task Groupings for Multi-Task Learning. - Chris Fifty; Ehsan Amid; Zhe Zhao 001; Tianhe Yu; Rohan Anil; Chelsea Finn (NeurIPS, 2021)

DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. - Hussein Hazimeh 001; Zhe Zhao 001; Aakanksha Chowdhery; Maheswaran Sathiamoorthy; Yihua Chen; Rahul Mazumder; Lichan Hong; Ed H. Chi (NeurIPS, 2021)

The Benchmark Lottery. - Mostafa Dehghani 001; Yi Tay; Alexey A. Gritsenko; Zhe Zhao 001; Neil Houlsby; Fernando Diaz 001; Donald Metzler; Oriol Vinyals (CoRR, 2021)

HyperPrompt: Prompt-based Task-Conditioning of Transformers. - Yun He; Huaixiu Steven Zheng; Yi Tay; Jai Prakash Gupta 001; Yu Du; Vamsi Aribandi; Zhe Zhao 001; YaGuang Li; Zhao Chen; Donald Metzler; Heng-Tze Cheng; Ed H. Chi (ICML, 2022)

Improving Multi-Task Generalization via Regularizing Spurious Correlation. - Ziniu Hu; Zhe Zhao 001; Xinyang Yi; Tiansheng Yao; Lichan Hong; Yizhou Sun; Ed H. Chi (NeurIPS, 2022)

Transformer Memory as a Differentiable Search Index. - Yi Tay; Vinh Tran 002; Mostafa Dehghani 001; Jianmo Ni; Dara Bahri; Harsh Mehta; Zhen Qin 001; Kai Hui 001; Zhe Zhao 001; Jai Prakash Gupta 001; Tal Schuster; William W. Cohen; et al. (NeurIPS, 2022)

Can Small Heads Help? Understanding and Improving Multi-Task Generalization. - Yuyan Wang; Zhe Zhao 001; Bo Dai 001; Christopher Fifty; Dong Lin; Lichan Hong; Li Wei; Ed H. Chi (WWW, 2022)

Multitask Ranking System for Immersive Feed and No More Clicks: A Case Study of Short-Form Video Recommendation. - Qingyun Liu 003; Zhe Zhao 001; Liang Liu 017; Zhen Zhang; Junjie Shan; Yuening Li; Shuchao Bi; Lichan Hong; Ed H. Chi (CIKM, 2023)

Fast as CHITA: Neural Network Pruning with Combinatorial Optimization. - Riade Benbaki; Wenyu Chen 003; Xiang Meng 004; Hussein Hazimeh 001; Natalia Ponomareva 001; Zhe Zhao 001; Rahul Mazumder (ICML, 2023)

COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search. - Shibal Ibrahim; Wenyu Chen 003; Hussein Hazimeh 001; Natalia Ponomareva 001; Zhe Zhao 001; Rahul Mazumder (KDD, 2023)

Talking Models: Distill Pre-trained Knowledge to Downstream Models via Interactive Communication. - Zhe Zhao 001; Qingyun Liu 003; Huan Gui; Bang An; Lichan Hong; Ed H. Chi (CoRR, 2023)

LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views. - Yuji Roh; Qingyun Liu 003; Huan Gui; Zhe Yuan; Yujin Tang; Steven Euijong Whang; Liang Liu 017; Shuchao Bi; Lichan Hong; Ed H. Chi; Zhe Zhao 001 (ICML, 2024)

Bridging the Gap: Unpacking the Hidden Challenges in Knowledge Distillation for Online Ranking Systems. - Nikhil Khani; Li Wei; Aniruddh Nath; Shawn Andrews; Shuo Yang; Yang Liu 136; Pendo Abbo; Maciej Kula; Jarrod Kahn; Zhe Zhao 001; Lichan Hong; Ed H. Chi (RecSys, 2024)

Learned Ranking Function: From Short-term Behavior Predictions to Long-term User Satisfaction. - Yi Wu; Daryl Chang; Jennifer She; Zhe Zhao 001; Li Wei; Lukasz Heldt (RecSys, 2024)

Co-optimize Content Generation and Consumption in a Large Scale Video Recommendation System. - Zhen Zhang; Qingyun Liu 003; Yuening Li; Sourabh Bansod; Mingyan Gao; Yaping Zhang; Zhe Zhao 001; Lichan Hong; Ed H. Chi; Shuchao Bi; Liang Liu 017 (RecSys, 2024)

Wisdom of Committee: Distilling from Foundation Model to Specialized Application Model. - Zichang Liu; Qingyun Liu 003; Yuening Li; Liang Liu 017; Anshumali Shrivastava; Shuchao Bi; Lichan Hong; Ed H. Chi; Zhe Zhao 001 (CoRR, 2024)

ReMem: Mutual Information-Aware Fine-tuning of Pretrained Vision Transformers for Effective Knowledge Distillation. - Chengyu Dong; Huan Gui; Noveen Sachdeva; Long Jin; Ke Yin; Jingbo Shang; Lichan Hong; Ed H. Chi; Zhe Zhao 001 (CoRR, 2025)