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ORCIDEd H. Chi
Ed Huai-hsin Chi – 紀懷新
2020 – today
- 2025
[i92]Yupeng Hou, Jianmo Ni, Zhankui He, Noveen Sachdeva, Wang-Cheng Kang, Ed H. Chi, Julian J. McAuley, Derek Zhiyuan Cheng:
ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation. CoRR abs/2502.13581 (2025)- 2024
- [j24]Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Alex Castro-Ros, Marie Pellat, Kevin Robinson, Dasha Valter, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Y. Zhao, Yanping Huang, Andrew M. Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei:
Scaling Instruction-Finetuned Language Models. J. Mach. Learn. Res. 25: 70:1-70:53 (2024) - [c192]Alicia Tsai, Adam Kraft, Long Jin, Chenwei Cai, Anahita Hosseini, Taibai Xu, Zemin Zhang, Lichan Hong, Ed Huai-hsin Chi, Xinyang Yi:
Leveraging LLM Reasoning Enhances Personalized Recommender Systems. ACL (Findings) 2024: 13176-13188 - [c191]Xiao Ma
, Swaroop Mishra, Ariel Liu, Sophie Ying Su, Jilin Chen, Chinmay Kulkarni, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi:
Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses. CHI Extended Abstracts 2024: 56:1-56:12 - [c190]Michihiro Yasunaga, Xinyun Chen, Yujia Li, Panupong Pasupat, Jure Leskovec, Percy Liang, Ed H. Chi, Denny Zhou:
Large Language Models as Analogical Reasoners. ICLR 2024 - [c189]Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V. Le, Denny Zhou:
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models. ICLR 2024 - [c188]Yuji Roh, Qingyun Liu, Huan Gui, Zhe Yuan, Yujin Tang, Steven Euijong Whang, Liang Liu, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao:
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views. ICML 2024 - [c187]Yi Su, Haokai Lu, Yuening Li, Liang Liu, Shuchao Bi, Ed H. Chi, Minmin Chen:
Multi-Task Neural Linear Bandit for Exploration in Recommender Systems. KDD 2024: 5723-5730 - [c186]Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan Hulikal Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy:
Aligning Large Language Models with Recommendation Knowledge. NAACL-HLT (Findings) 2024: 1051-1066 - [c185]Pei Zhou, Jay Pujara, Xiang Ren, Xinyun Chen, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou, Swaroop Mishra, Huaixiu Steven Zheng:
SELF-DISCOVER: Large Language Models Self-Compose Reasoning Structures. NeurIPS 2024 - [c184]Nikhil Khani, Li Wei, Aniruddh Nath, Shawn Andrews, Shuo Yang, Yang Liu, Pendo Abbo, Maciej Kula, Jarrod Kahn, Zhe Zhao, Lichan Hong, Ed H. Chi:
Bridging the Gap: Unpacking the Hidden Challenges in Knowledge Distillation for Online Ranking Systems. RecSys 2024: 758-761 - [c183]Zhen Zhang, Qingyun Liu, Yuening Li, Sourabh Bansod, Mingyan Gao, Yaping Zhang, Zhe Zhao, Lichan Hong, Ed H. Chi, Shuchao Bi, Liang Liu:
Co-optimize Content Generation and Consumption in a Large Scale Video Recommendation System. RecSys 2024: 762-764 - [c182]Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, James Caverlee, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Improving Data Efficiency for Recommenders and LLMs. RecSys 2024: 790-792 - [c181]Yin Zhang, Ruoxi Wang, Xiang Li, Tiansheng Yao, Andrew Evdokimov, Jonathan Valverde, Yuan Gao, Jerry Zhang, Evan Ettinger, Ed H. Chi, Derek Zhiyuan Cheng:
Self-Auxiliary Distillation for Sample Efficient Learning in Google-Scale Recommenders. RecSys 2024: 829-831 - [c180]Yuening Li, Diego Uribe, Chuan He, Jiaxi Tang, Qingyun Liu, Junjie Shan, Ben Most, Kaushik Kalyan, Shuchao Bi, Xinyang Yi, Lichan Hong, Ed H. Chi, Liang Liu:
Short-form Video Needs Long-term Interests: An Industrial Solution for Serving Large User Sequence Models. RecSys 2024: 832-834 - [c179]Jianling Wang, Haokai Lu, Yifan Liu, He Ma, Yueqi Wang, Yang Gu, Shuzhou Zhang, Ningren Han, Shuchao Bi, Lexi Baugher, Ed H. Chi, Minmin Chen:
LLMs for User Interest Exploration in Large-scale Recommendation Systems. RecSys 2024: 872-877 - [c178]Anima Singh, Trung Vu, Nikhil Mehta, Raghunandan H. Keshavan, Maheswaran Sathiamoorthy, Yilin Zheng, Lichan Hong, Lukasz Heldt, Li Wei, Devansh Tandon, Ed H. Chi, Xinyang Yi:
Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations. RecSys 2024: 1039-1044 - [c177]Yi Su, Xiangyu Wang, Elaine Ya Le, Liang Liu, Yuening Li, Haokai Lu, Benjamin Lipshitz, Sriraj Badam, Lukasz Heldt, Shuchao Bi, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen:
Long-Term Value of Exploration: Measurements, Findings and Algorithms. WSDM 2024: 636-644 - [c176]Bo Chang, Changping Meng, He Ma, Shuo Chang, Yang Gu, Yajun Peng, Jingchen Feng, Yaping Zhang, Shuchao Bi, Ed H. Chi, Minmin Chen:
Cluster Anchor Regularization to Alleviate Popularity Bias in Recommender Systems. WWW (Companion Volume) 2024: 151-160 - [c175]Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen:
Large Language Models as Data Augmenters for Cold-Start Item Recommendation. WWW (Companion Volume) 2024: 726-729 - [i91]Pei Zhou, Jay Pujara, Xiang Ren, Xinyun Chen, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou, Swaroop Mishra, Huaixiu Steven Zheng:
Self-Discover: Large Language Models Self-Compose Reasoning Structures. CoRR abs/2402.03620 (2024) - [i90]Yuji Roh, Qingyun Liu, Huan Gui, Zhe Yuan, Yujin Tang, Steven Euijong Whang, Liang Liu, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao:
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views. CoRR abs/2402.04644 (2024) - [i89]Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, Lichan Hong, Ed H. Chi, James Caverlee, Julian J. McAuley, Derek Zhiyuan Cheng:
How to Train Data-Efficient LLMs. CoRR abs/2402.09668 (2024) - [i88]Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen:
Large Language Models as Data Augmenters for Cold-Start Item Recommendation. CoRR abs/2402.11724 (2024) - [i87]Zichang Liu, Qingyun Liu, Yuening Li, Liang Liu, Anshumali Shrivastava, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao:
Wisdom of Committee: Distilling from Foundation Model to Specialized Application Model. CoRR abs/2402.14035 (2024) - [i86]Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan H. Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy:
Aligning Large Language Models with Recommendation Knowledge. CoRR abs/2404.00245 (2024) - [i85]Yuyan Wang, Cheenar Banerjee, Samer Chucri, Fabio Soldo, Sriraj Badam, Ed H. Chi, Minmin Chen:
Diversifying by Intent in Recommender Systems. CoRR abs/2405.12327 (2024) - [i84]Jianling Wang, Haokai Lu, Yifan Liu, He Ma, Yueqi Wang, Yang Gu, Shuzhou Zhang, Ningren Han, Shuchao Bi, Lexi Baugher, Ed H. Chi, Minmin Chen:
LLMs for User Interest Exploration: A Hybrid Approach. CoRR abs/2405.16363 (2024) - [i83]Huaixiu Steven Zheng, Swaroop Mishra, Hugh Zhang, Xinyun Chen, Minmin Chen, Azade Nova, Le Hou, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou:
NATURAL PLAN: Benchmarking LLMs on Natural Language Planning. CoRR abs/2406.04520 (2024) - [i82]Alicia Tsai, Adam Kraft, Long Jin, Chenwei Cai, Anahita Hosseini, Taibai Xu, Zemin Zhang, Lichan Hong, Ed H. Chi, Xinyang Yi:
Leveraging LLM Reasoning Enhances Personalized Recommender Systems. CoRR abs/2408.00802 (2024) - [i81]Nikhil Khani, Shuo Yang, Aniruddh Nath, Yang Liu, Pendo Abbo, Li Wei, Shawn Andrews, Maciej Kula, Jarrod Kahn, Zhe Zhao, Lichan Hong, Ed H. Chi:
Bridging the Gap: Unpacking the Hidden Challenges in Knowledge Distillation for Online Ranking Systems. CoRR abs/2408.14678 (2024) - [i80]Kiran Vodrahalli, Santiago Ontanon, Nilesh Tripuraneni, Kelvin Xu, Sanil Jain, Rakesh Shivanna, Jeffrey Hui, Nishanth Dikkala, Mehran Kazemi, Bahare Fatemi, Rohan Anil, Ethan Dyer, Siamak Shakeri, Roopali Vij, Harsh Mehta, Vinay V. Ramasesh, Quoc Le, Ed H. Chi, Yifeng Lu, Orhan Firat, Angeliki Lazaridou, Jean-Baptiste Lespiau, Nithya Attaluri, Kate Olszewska:
Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries. CoRR abs/2409.12640 (2024) - [i79]Allen Nie, Yi Su, Bo Chang, Jonathan N. Lee, Ed H. Chi, Quoc V. Le, Minmin Chen:
EVOLvE: Evaluating and Optimizing LLMs For Exploration. CoRR abs/2410.06238 (2024) - [i78]Dong-Ho Lee, Adam Kraft, Long Jin, Nikhil Mehta, Taibai Xu, Lichan Hong, Ed H. Chi, Xinyang Yi:
STAR: A Simple Training-free Approach for Recommendations using Large Language Models. CoRR abs/2410.16458 (2024) - 2023
- [c174]Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed H. Chi, Denny Zhou, Jason Wei:
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. ACL (Findings) 2023: 13003-13051 - [c173]Qingyun Liu, Zhe Zhao, Liang Liu, Zhen Zhang, Junjie Shan, Yuening Li, Shuchao Bi, Lichan Hong, Ed H. Chi:
Multitask Ranking System for Immersive Feed and No More Clicks: A Case Study of Short-Form Video Recommendation. CIKM 2023: 4709-4716 - [c172]Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Ed H. Chi, Jilin Chen, Alex Beutel:
Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation. EMNLP (Findings) 2023: 127-139 - [c171]Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, Denny Zhou:
Self-Consistency Improves Chain of Thought Reasoning in Language Models. ICLR 2023 - [c170]Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, Ed H. Chi:
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. ICLR 2023 - [c169]Freda Shi, Xinyun Chen, Kanishka Misra, Nathan Scales, David Dohan, Ed H. Chi, Nathanael Schärli, Denny Zhou:
Large Language Models Can Be Easily Distracted by Irrelevant Context. ICML 2023: 31210-31227 - [c168]Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi:
Improving Training Stability for Multitask Ranking Models in Recommender Systems. KDD 2023: 4882-4893 - [c167]Jianling Wang, Haokai Lu, Sai Zhang, Bart N. Locanthi, Haoting Wang, Dylan Greaves, Benjamin Lipshitz, Sriraj Badam, Ed H. Chi, Cristos J. Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen:
Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation. KDD 2023: 5082-5091 - [c166]Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi:
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). KDD 2023: 5608-5617 - [c165]Derek Zhiyuan Cheng, Dhaval Patel, Linsey Pang, Sameep Mehta, Kexin Xie, Ed H. Chi, Wei Liu, Nitesh V. Chawla, James Bailey:
Foundations and Applications in Large-scale AI Models: Pre-training, Fine-tuning, and Prompt-based Learning. KDD 2023: 5853-5854 - [c164]Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. NeurIPS 2023 - [c163]Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan Hulikal Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Mahesh Sathiamoorthy:
Recommender Systems with Generative Retrieval. NeurIPS 2023 - [c162]Derek Zhiyuan Cheng, Ruoxi Wang, Wang-Cheng Kang, Benjamin Coleman, Yin Zhang, Jianmo Ni, Jonathan Valverde, Lichan Hong, Ed H. Chi:
Efficient Data Representation Learning in Google-scale Systems. RecSys 2023: 267-271 - [c161]Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi:
Online Matching: A Real-time Bandit System for Large-scale Recommendations. RecSys 2023: 403-414 - [c160]Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel:
What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel. SaTML 2023: 365-376 - [c159]Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng:
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. SIGIR 2023: 2062-2066 - [c158]Bo Chang, Alexandros Karatzoglou, Yuyan Wang, Can Xu, Ed H. Chi, Minmin Chen:
Latent User Intent Modeling for Sequential Recommenders. WWW (Companion Volume) 2023: 427-431 - [c157]Abhishek Naik, Bo Chang, Alexandros Karatzoglou, Martin Mladenov, Ed H. Chi, Minmin Chen:
Investigating Action-Space Generalization in Reinforcement Learning for Recommendation Systems. WWW (Companion Volume) 2023: 966-972 - [i77]Freda Shi, Xinyun Chen, Kanishka Misra, Nathan Scales, David Dohan, Ed H. Chi, Nathanael Schärli, Denny Zhou:
Large Language Models Can Be Easily Distracted by Irrelevant Context. CoRR abs/2302.00093 (2023) - [i76]Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi:
Improving Training Stability for Multitask Ranking Models in Recommender Systems. CoRR abs/2302.09178 (2023) - [i75]Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel:
What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel. CoRR abs/2302.11188 (2023) - [i74]Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan H. Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Maheswaran Sathiamoorthy:
Recommender Systems with Generative Retrieval. CoRR abs/2305.05065 (2023) - [i73]Wang-Cheng Kang, Jianmo Ni, Nikhil Mehta, Maheswaran Sathiamoorthy, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction. CoRR abs/2305.06474 (2023) - [i72]Yi Su, Xiangyu Wang, Elaine Ya Le, Liang Liu, Yuening Li, Haokai Lu, Benjamin Lipshitz, Sriraj Badam, Lukasz Heldt, Shuchao Bi, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen:
Value of Exploration: Measurements, Findings and Algorithms. CoRR abs/2305.07764 (2023) - [i71]Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. CoRR abs/2305.12102 (2023) - [i70]Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Jilin Chen, Ed H. Chi, Alex Beutel:
Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals. CoRR abs/2305.13535 (2023) - [i69]Konstantina Christakopoulou, Alberto Lalama, Cj Adams, Iris Qu, Yifat Amir, Samer Chucri, Pierce Vollucci, Fabio Soldo, Dina Bseiso, Sarah Scodel, Lucas Dixon, Ed H. Chi, Minmin Chen:
Large Language Models for User Interest Journeys. CoRR abs/2305.15498 (2023) - [i68]Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng:
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. CoRR abs/2305.17386 (2023) - [i67]Pan Li, Yuyan Wang, Ed H. Chi, Minmin Chen:
Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations. CoRR abs/2306.01475 (2023) - [i66]Pan Li, Yuyan Wang, Ed H. Chi, Minmin Chen:
Hierarchical Reinforcement Learning for Modeling User Novelty-Seeking Intent in Recommender Systems. CoRR abs/2306.01476 (2023) - [i65]Jianling Wang, Haokai Lu, Sai Zhang, Bart N. Locanthi, Haoting Wang, Dylan Greaves, Benjamin Lipshitz, Sriraj Badam, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen:
Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation. CoRR abs/2306.01720 (2023) - [i64]Anima Singh, Trung Vu, Raghunandan H. Keshavan, Nikhil Mehta, Xinyang Yi, Lichan Hong, Lukasz Heldt, Li Wei, Ed H. Chi, Maheswaran Sathiamoorthy:
Better Generalization with Semantic IDs: A case study in Ranking for Recommendations. CoRR abs/2306.08121 (2023) - [i63]Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi:
Online Matching: A Real-time Bandit System for Large-scale Recommendations. CoRR abs/2307.15893 (2023) - [i62]Nikhil Mehta, Anima Singh, Xinyang Yi, Sagar Jain, Lichan Hong, Ed H. Chi:
Density Weighting for Multi-Interest Personalized Recommendation. CoRR abs/2308.01563 (2023) - [i61]Michihiro Yasunaga, Xinyun Chen, Yujia Li, Panupong Pasupat, Jure Leskovec, Percy Liang, Ed H. Chi, Denny Zhou:
Large Language Models as Analogical Reasoners. CoRR abs/2310.01714 (2023) - [i60]Zhe Zhao, Qingyun Liu, Huan Gui, Bang An, Lichan Hong, Ed H. Chi:
Talking Models: Distill Pre-trained Knowledge to Downstream Models via Interactive Communication. CoRR abs/2310.03188 (2023) - [i59]Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V. Le, Denny Zhou:
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models. CoRR abs/2310.06117 (2023) - [i58]Huan Gui, Ruoxi Wang, Ke Yin, Long Jin, Maciej Kula, Taibai Xu, Lichan Hong, Ed H. Chi:
Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems. CoRR abs/2311.05884 (2023) - [i57]Xiao Ma, Swaroop Mishra, Ariel Liu, Sophie Ying Su, Jilin Chen, Chinmay Kulkarni, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi:
Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses. CoRR abs/2312.00763 (2023) - 2022
- [j23]Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus:
Emergent Abilities of Large Language Models. Trans. Mach. Learn. Res. 2022 (2022) - [c156]Yun He, Huaixiu Steven Zheng, Yi Tay, Jai Prakash Gupta, Yu Du, Vamsi Aribandi, Zhe Zhao, YaGuang Li, Zhao Chen, Donald Metzler, Heng-Tze Cheng, Ed H. Chi:
HyperPrompt: Prompt-based Task-Conditioning of Transformers. ICML 2022: 8678-8690 - [c155]Yuyan Wang, Mohit Sharma, Can Xu, Sriraj Badam, Qian Sun, Lee Richardson, Lisa Chung, Ed H. Chi, Minmin Chen:
Surrogate for Long-Term User Experience in Recommender Systems. KDD 2022: 4100-4109 - [c154]Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed H. Chi:
Improving Multi-Task Generalization via Regularizing Spurious Correlation. NeurIPS 2022 - [c153]Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, Denny Zhou:
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. NeurIPS 2022 - [c152]Minmin Chen, Can Xu, Vince Gatto, Devanshu Jain, Aviral Kumar, Ed H. Chi:
Off-Policy Actor-critic for Recommender Systems. RecSys 2022: 338-349 - [c151]Furkan Kocayusufoglu, Tao Wu, Anima Singh, Georgios Roumpos, Heng-Tze Cheng, Sagar Jain, Ed H. Chi, Ambuj K. Singh:
Multi-Resolution Attention for Personalized Item Search. WSDM 2022: 508-516 - [c150]Jianling Wang, Ya Le, Bo Chang, Yuyan Wang, Ed H. Chi, Minmin Chen:
Learning to Augment for Casual User Recommendation. WWW 2022: 2183-2194 - [c149]Yuyan Wang, Zhe Zhao, Bo Dai, Christopher Fifty, Dong Lin, Lichan Hong, Li Wei, Ed H. Chi:
Can Small Heads Help? Understanding and Improving Multi-Task Generalization. WWW 2022: 3009-3019 - [c148]Hongyi Wen, Xinyang Yi, Tiansheng Yao, Jiaxi Tang, Lichan Hong, Ed H. Chi:
Distributionally-robust Recommendations for Improving Worst-case User Experience. WWW 2022: 3606-3610 - [i56]Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Kathleen S. Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Agüera y Arcas, Claire Cui, Marian Croak, Ed H. Chi, Quoc Le:
LaMDA: Language Models for Dialog Applications. CoRR abs/2201.08239 (2022) - [i55]Bo Chang, Can Xu, Matthieu Lê, Jingchen Feng, Ya Le, Sriraj Badam, Ed H. Chi, Minmin Chen:
Recency Dropout for Recurrent Recommender Systems. CoRR abs/2201.11016 (2022) - [i54]Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed H. Chi, Quoc Le, Denny Zhou:
Chain of Thought Prompting Elicits Reasoning in Large Language Models. CoRR abs/2201.11903 (2022) - [i53]Kiran Vodrahalli, Rakesh Shivanna, Maheswaran Sathiamoorthy, Sagar Jain, Ed H. Chi:
Algorithms for Efficiently Learning Low-Rank Neural Networks. CoRR abs/2202.00834 (2022) - [i52]Yun He, Huaixiu Steven Zheng, Yi Tay, Jai Prakash Gupta, Yu Du, Vamsi Aribandi, Zhe Zhao, YaGuang Li, Zhao Chen, Donald Metzler, Heng-Tze Cheng, Ed H. Chi:
HyperPrompt: Prompt-based Task-Conditioning of Transformers. CoRR abs/2203.00759 (2022) - [i51]Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou:
Self-Consistency Improves Chain of Thought Reasoning in Language Models. CoRR abs/2203.11171 (2022) - [i50]Jianling Wang, Ya Le, Bo Chang, Yuyan Wang, Ed H. Chi, Minmin Chen:
Learning to Augment for Casual User Recommendation. CoRR abs/2204.00926 (2022) - [i49]Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed H. Chi:
Improving Multi-Task Generalization via Regularizing Spurious Correlation. CoRR abs/2205.09797 (2022) - [i48]Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, Ed H. Chi:
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. CoRR abs/2205.10625 (2022) - [i47]Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus:
Emergent Abilities of Large Language Models. CoRR abs/2206.07682 (2022) - [i46]Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou:
Rationale-Augmented Ensembles in Language Models. CoRR abs/2207.00747 (2022) - [i45]Konstantina Christakopoulou, Can Xu, Sai Zhang, Sriraj Badam, Trevor Potter, Daniel Li, Hao Wan, Xinyang Yi, Ya Le, Chris Berg, Eric Bencomo Dixon, Ed H. Chi, Minmin Chen:
Reward Shaping for User Satisfaction in a REINFORCE Recommender. CoRR abs/2209.15166 (2022) - [i44]Flavien Prost, Ben Packer, Jilin Chen, Li Wei, Pierre Kremp, Nick Blumm, Susan Wang, Tulsee Doshi, Tonia Osadebe, Lukasz Heldt, Ed H. Chi, Alex Beutel:
Simpson's Paradox in Recommender Fairness: Reconciling differences between per-user and aggregated evaluations. CoRR abs/2210.07755 (2022) - [i43]Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed H. Chi, Denny Zhou, Jason Wei:
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. CoRR abs/2210.09261 (2022) - [i42]Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Y. Zhao, Yanping Huang, Andrew M. Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei:
Scaling Instruction-Finetuned Language Models. CoRR abs/2210.11416 (2022) - [i41]Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi:
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). CoRR abs/2210.14309 (2022) - [i40]Bo Chang, Alexandros Karatzoglou, Yuyan Wang, Can Xu, Ed H. Chi, Minmin Chen:
Latent User Intent Modeling for Sequential Recommenders. CoRR abs/2211.09832 (2022) - 2021
- [c147]Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel:
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. AIES 2021: 873-883 - [c146]Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei:
Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. AISTATS 2021: 928-936 - [c145]Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Ting Chen, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi (Jay) Kang, Evan Ettinger:
Self-supervised Learning for Large-scale Item Recommendations. CIKM 2021: 4321-4330 - [c144]Ananth Balashankar, Xuezhi Wang, Ben Packer, Nithum Thain, Ed H. Chi, Alex Beutel:
Can We Improve Model Robustness through Secondary Attribute Counterfactuals? EMNLP (1) 2021: 4701-4712 - [c143]Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed H. Chi, Honglak Lee, Minmin Chen:
Batch Reinforcement Learning Through Continuation Method. ICLR 2021 - [c142]Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H. Chi:
Learning to Embed Categorical Features without Embedding Tables for Recommendation. KDD 2021: 840-850 - [c141]Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi:
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. KDD 2021: 1748-1757 - [c140]Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi:
Improving Calibration through the Relationship with Adversarial Robustness. NeurIPS 2021: 14358-14369 - [c139]Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi:
DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. NeurIPS 2021: 29335-29347 - [c138]Minmin Chen, Yuyan Wang, Can Xu, Ya Le, Mohit Sharma, Lee Richardson, Su-Lin Wu, Ed H. Chi:
Values of User Exploration in Recommender Systems. RecSys 2021: 85-95 - [c137]Zhe Chen, Yuyan Wang, Dong Lin, Derek Zhiyuan Cheng, Lichan Hong, Ed H. Chi, Claire Cui:
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems. WSDM 2021: 76-84 - [c136]Minmin Chen, Bo Chang, Can Xu, Ed H. Chi:
User Response Models to Improve a REINFORCE Recommender System. WSDM 2021: 121-129 - [c135]Xuezhi Wang, Nithum Thain, Anu Sinha, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel:
Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems. WSDM 2021: 436-444 - [c134]Ruoxi Wang, Rakesh Shivanna, Derek Zhiyuan Cheng, Sagar Jain, Dong Lin, Lichan Hong, Ed H. Chi:
DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems. WWW 2021: 1785-1797 - [c133]Yin Zhang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, Ed H. Chi:
A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. WWW 2021: 2220-2231 - [c132]Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen:
Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities. WWW 2021: 3872-3883 - [i39]Sirui Yao, Yoni Halpern, Nithum Thain, Xuezhi Wang, Kang Lee, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel:
Measuring Recommender System Effects with Simulated Users. CoRR abs/2101.04526 (2021) - [i38]Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen:
Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities. CoRR abs/2105.02377 (2021) - [i37]Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel:
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. CoRR abs/2105.09985 (2021) - [i36]Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi:
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. CoRR abs/2106.02705 (2021) - [i35]Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi:
DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. CoRR abs/2106.03760 (2021) - 2020
- [c131]Tao Wu, Ellie Ka In Chio, Heng-Tze Cheng, Yu Du, Steffen Rendle, Dima Kuzmin, Ritesh Agarwal, Li Zhang, John R. Anderson, Sarvjeet Singh, Tushar Chandra, Ed H. Chi, Wen Li, Ankit Kumar, Xiang Ma, Alex Soares, Nitin Jindal, Pei Cao:
Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval. CIKM 2020: 2821-2828 - [c130]Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, Ed H. Chi:
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation. EMNLP (1) 2020: 5141-5146 - [c129]Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier:
BRPO: Batch Residual Policy Optimization. IJCAI 2020: 2824-2830 - [c128]Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi:
Fairness without Demographics through Adversarially Reweighted Learning. NeurIPS 2020 - [c127]Konstantina Christakopoulou, Madeleine Traverse, Trevor Potter, Emma Marriott, Daniel Li, Chris Haulk, Ed H. Chi, Minmin Chen:
Deconfounding User Satisfaction Estimation from Response Rate Bias. RecSys 2020: 450-455 - [c126]Ed H. Chi:
From Missing Data to Boltzmann Distributions and Time Dynamics: The Statistical Physics of Recommendation. WSDM 2020: 1-2 - [c125]Ji Yang, Xinyang Yi, Derek Zhiyuan Cheng, Lichan Hong, Yang Li, Simon Xiaoming Wang, Taibai Xu, Ed H. Chi:
Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations. WWW (Companion Volume) 2020: 441-447 - [c124]Jiaqi Ma, Zhe Zhao, Xinyang Yi, Ji Yang, Minmin Chen, Jiaxi Tang, Lichan Hong, Ed H. Chi:
Off-policy Learning in Two-stage Recommender Systems. WWW 2020: 463-473 - [c123]Wang-Cheng Kang, Derek Zhiyuan Cheng, Ting Chen, Xinyang Yi, Dong Lin, Lichan Hong, Ed H. Chi:
Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems. WWW (Companion Volume) 2020: 562-566 - [c122]Jyun-Yu Jiang, Tao Wu, Georgios Roumpos, Heng-Tze Cheng, Xinyang Yi, Ed H. Chi, Harish Ganapathy, Nitin Jindal, Pei Cao, Wei Wang:
End-to-End Deep Attentive Personalized Item Retrieval for Online Content-sharing Platforms. WWW 2020: 2870-2877 - [i34]Jiaxi Tang, Rakesh Shivanna, Zhe Zhao, Dong Lin, Anima Singh, Ed H. Chi, Sagar Jain:
Understanding and Improving Knowledge Distillation. CoRR abs/2002.03532 (2020) - [i33]Ge Liu, Rui Wu, Heng-Tze Cheng, Jing Wang, Jayden Ooi, Lihong Li, Ang Li, Wai Lok Sibon Li, Craig Boutilier, Ed H. Chi:
Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing. CoRR abs/2002.05229 (2020) - [i32]Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier:
BRPO: Batch Residual Policy Optimization. CoRR abs/2002.05522 (2020) - [i31]Wang-Cheng Kang, Derek Zhiyuan Cheng, Ting Chen, Xinyang Yi, Dong Lin, Lichan Hong, Ed H. Chi:
Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems. CoRR abs/2002.08530 (2020) - [i30]Carole-Jean Wu, Robin Burke, Ed H. Chi, Joseph A. Konstan, Julian J. McAuley, Yves Raimond, Hao Zhang:
Developing a Recommendation Benchmark for MLPerf Training and Inference. CoRR abs/2003.07336 (2020) - [i29]Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei:
Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. CoRR abs/2006.05067 (2020) - [i28]Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi:
Fairness without Demographics through Adversarially Reweighted Learning. CoRR abs/2006.13114 (2020) - [i27]Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi:
Improving Uncertainty Estimates through the Relationship with Adversarial Robustness. CoRR abs/2006.16375 (2020) - [i26]Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi Kang, Evan Ettinger:
Self-supervised Learning for Deep Models in Recommendations. CoRR abs/2007.12865 (2020) - [i25]Tao Wu, Ellie Ka In Chio, Heng-Tze Cheng, Yu Du, Steffen Rendle, Dima Kuzmin, Ritesh Agarwal, Li Zhang, John R. Anderson, Sarvjeet Singh, Tushar Chandra, Ed H. Chi, Wen Li, Ankit Kumar, Xiang Ma, Alex Soares, Nitin Jindal, Pei Cao:
Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval. CoRR abs/2008.02930 (2020) - [i24]Yuyan Wang, Zhe Zhao, Bo Dai, Christopher Fifty, Dong Lin, Lichan Hong, Ed H. Chi:
Small Towers Make Big Differences. CoRR abs/2008.05808 (2020) - [i23]Zhe Chen, Yuyan Wang, Dong Lin, Derek Zhiyuan Cheng, Lichan Hong, Ed H. Chi, Claire Cui:
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems. CoRR abs/2008.07032 (2020) - [i22]Ruoxi Wang, Rakesh Shivanna, Derek Zhiyuan Cheng, Sagar Jain, Dong Lin, Lichan Hong, Ed H. Chi:
DCN-M: Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems. CoRR abs/2008.13535 (2020) - [i21]Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, Ed H. Chi:
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation. CoRR abs/2010.02338 (2020) - [i20]Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H. Chi:
Deep Hash Embedding for Large-Vocab Categorical Feature Representations. CoRR abs/2010.10784 (2020) - [i19]Yin Zhang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, Ed H. Chi:
A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. CoRR abs/2010.15982 (2020) - [i18]Hussam Abu-Libdeh, Deniz Altinbüken, Alex Beutel, Ed H. Chi, Lyric Doshi, Tim Kraska, Xiaozhou Li, Andy Ly, Christopher Olston:
Learned Indexes for a Google-scale Disk-based Database. CoRR abs/2012.12501 (2020)
2010 – 2019
- 2019
- [c121]Jiaqi Ma, Zhe Zhao, Jilin Chen, Ang Li, Lichan Hong, Ed H. Chi:
SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning. AAAI 2019: 216-223 - [c120]Sahaj Garg, Vincent Perot, Nicole Limtiaco, Ankur Taly, Ed H. Chi, Alex Beutel:
Counterfactual Fairness in Text Classification through Robustness. AIES 2019: 219-226 - [c119]Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Allison Woodruff, Christine Luu, Pierre Kreitmann, Jonathan Bischof, Ed H. Chi:
Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements. AIES 2019: 453-459 - [c118]Tim Kraska, Mohammad Alizadeh, Alex Beutel, Ed H. Chi, Ani Kristo, Guillaume Leclerc, Samuel Madden, Hongzi Mao, Vikram Nathan:
SageDB: A Learned Database System. CIDR 2019 - [c117]Bo Chang, Minmin Chen, Eldad Haber, Ed H. Chi:
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks. ICLR (Poster) 2019 - [c116]Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson:
Efficient Training on Very Large Corpora via Gramian Estimation. ICLR (Poster) 2019 - [c115]Francois Belletti, Minmin Chen, Ed H. Chi:
Quantifying Long Range Dependence in Language and User Behavior to improve RNNs. KDD 2019: 1317-1327 - [c114]Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, Cristos Goodrow:
Fairness in Recommendation Ranking through Pairwise Comparisons. KDD 2019: 2212-2220 - [c113]Zhe Zhao, Lichan Hong, Li Wei, Jilin Chen, Aniruddh Nath, Shawn Andrews, Aditee Kumthekar, Maheswaran Sathiamoorthy, Xinyang Yi, Ed H. Chi:
Recommending what video to watch next: a multitask ranking system. RecSys 2019: 43-51 - [c112]Xinyang Yi, Ji Yang, Lichan Hong, Derek Zhiyuan Cheng, Lukasz Heldt, Aditee Kumthekar, Zhe Zhao, Li Wei, Ed H. Chi:
Sampling-bias-corrected neural modeling for large corpus item recommendations. RecSys 2019: 269-277 - [c111]Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed H. Chi:
Top-K Off-Policy Correction for a REINFORCE Recommender System. WSDM 2019: 456-464 - [c110]Jiaxi Tang, Francois Belletti, Sagar Jain, Minmin Chen, Alex Beutel, Can Xu, Ed H. Chi:
Towards Neural Mixture Recommender for Long Range Dependent User Sequences. WWW 2019: 1782-1793 - [i17]Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Allison Woodruff, Christine Luu, Pierre Kreitmann, Jonathan Bischof, Ed H. Chi:
Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements. CoRR abs/1901.04562 (2019) - [i16]Dar Gilboa, Bo Chang, Minmin Chen, Greg Yang, Samuel S. Schoenholz, Ed H. Chi, Jeffrey Pennington:
Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs. CoRR abs/1901.08987 (2019) - [i15]Jiaxi Tang, Francois Belletti, Sagar Jain, Minmin Chen, Alex Beutel, Can Xu, Ed H. Chi:
Towards Neural Mixture Recommender for Long Range Dependent User Sequences. CoRR abs/1902.08588 (2019) - [i14]Bo Chang, Minmin Chen, Eldad Haber, Ed H. Chi:
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks. CoRR abs/1902.09689 (2019) - [i13]Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, Cristos Goodrow:
Fairness in Recommendation Ranking through Pairwise Comparisons. CoRR abs/1903.00780 (2019) - [i12]Francois Belletti, Minmin Chen, Ed H. Chi:
Quantifying Long Range Dependence in Language and User Behavior to improve RNNs. CoRR abs/1905.09414 (2019) - [i11]Candice Schumann, Xuezhi Wang, Alex Beutel, Jilin Chen, Hai Qian, Ed H. Chi:
Transfer of Machine Learning Fairness across Domains. CoRR abs/1906.09688 (2019) - [i10]Flavien Prost, Hai Qian, Qiuwen Chen, Ed H. Chi, Jilin Chen, Alex Beutel:
Toward a better trade-off between performance and fairness with kernel-based distribution matching. CoRR abs/1910.11779 (2019) - [i9]Xuezhi Wang, Nithum Thain, Anu Sinha, Ed H. Chi, Jilin Chen, Alex Beutel:
Practical Compositional Fairness: Understanding Fairness in Multi-Task ML Systems. CoRR abs/1911.01916 (2019) - 2018
- [j22]Amy X. Zhang, Jilin Chen, Wei Chai, Jinjun Xu, Lichan Hong, Ed H. Chi:
Evaluation and Refinement of Clustered Search Results with the Crowd. ACM Trans. Interact. Intell. Syst. 8(2): 14:1-14:28 (2018) - [c109]Francois Belletti, Alex Beutel, Sagar Jain, Ed Huai-hsin Chi:
Factorized Recurrent Neural Architectures for Longer Range Dependence. AISTATS 2018: 1522-1530 - [c108]Mark Wilhelm, Ajith Ramanathan, Alexander Bonomo, Sagar Jain, Ed H. Chi, Jennifer Gillenwater:
Practical Diversified Recommendations on YouTube with Determinantal Point Processes. CIKM 2018: 2165-2173 - [c107]Konstantina Christakopoulou, Alex Beutel, Rui Li, Sagar Jain, Ed H. Chi:
Q&R: A Two-Stage Approach toward Interactive Recommendation. KDD 2018: 139-148 - [c106]Jiaqi Ma, Zhe Zhao, Xinyang Yi, Jilin Chen, Lichan Hong, Ed H. Chi:
Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts. KDD 2018: 1930-1939 - [c105]Qian Zhao, Jilin Chen, Minmin Chen, Sagar Jain, Alex Beutel, Francois Belletti, Ed H. Chi:
Categorical-attributes-based item classification for recommender systems. RecSys 2018: 320-328 - [c104]Tim Kraska, Alex Beutel, Ed H. Chi, Jeffrey Dean, Neoklis Polyzotis:
The Case for Learned Index Structures. SIGMOD Conference 2018: 489-504 - [c103]Alex Beutel, Paul Covington, Sagar Jain, Can Xu, Jia Li, Vince Gatto, Ed H. Chi:
Latent Cross: Making Use of Context in Recurrent Recommender Systems. WSDM 2018: 46-54 - [i8]Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson:
Efficient Training on Very Large Corpora via Gramian Estimation. CoRR abs/1807.07187 (2018) - [i7]Sahaj Garg, Vincent Perot, Nicole Limtiaco, Ankur Taly, Ed H. Chi, Alex Beutel:
Counterfactual Fairness in Text Classification through Robustness. CoRR abs/1809.10610 (2018) - [i6]Irwan Bello, Sayali Kulkarni, Sagar Jain, Craig Boutilier, Ed Huai-hsin Chi, Elad Eban, Xiyang Luo, Alan Mackey, Ofer Meshi:
Seq2Slate: Re-ranking and Slate Optimization with RNNs. CoRR abs/1810.02019 (2018) - [i5]Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed H. Chi:
Top-K Off-Policy Correction for a REINFORCE Recommender System. CoRR abs/1812.02353 (2018) - 2017
- [j21]Ed H. Chi:
Technical perspective: Humans and computers working together on hard tasks. Commun. ACM 60(9): 92 (2017) - [c102]Alex Beutel, Ed Huai-hsin Chi, Zhiyuan Cheng, Hubert Pham, John R. Anderson:
Beyond Globally Optimal: Focused Learning for Improved Recommendations. WWW 2017: 203-212 - [i4]Alex Beutel, Jilin Chen, Zhe Zhao, Ed H. Chi:
Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations. CoRR abs/1707.00075 (2017) - [i3]Tim Kraska, Alex Beutel, Ed H. Chi, Jeffrey Dean, Neoklis Polyzotis:
The Case for Learned Index Structures. CoRR abs/1712.01208 (2017) - 2016
- [c101]Andrew Warr, Ed H. Chi, Helen Harris, Alexander Kuscher, Jenn Chen, Robert Flack, Nicholas Jitkoff:
Window Shopping: A Study of Desktop Window Switching. CHI 2016: 3335-3338 - [c100]Rong Yang, Sarvjeet Singh, Pei Cao, Ed H. Chi, Bo Fu:
Video Watch Time and Comment Sentiment: Experiences from YouTube. HotWeb 2016: 26-28 - [c99]Shuo Chang, Peng Dai, Lichan Hong, Cheng Sheng, Tianjiao Zhang, Ed H. Chi:
AppGrouper: Knowledge-based Interactive Clustering Tool for App Search Results. IUI 2016: 348-358 - 2015
- [j20]Ben Steichen, Nicola Ferro, David Lewis, Ed H. Chi:
1st International Workshop on Multilingual Web Access (MWA 2015). SIGIR Forum 49(2): 137-140 (2015) - [c98]Daniel M. Russell, Jaime Teevan, Meredith Ringel Morris, Marti A. Hearst, Ed H. Chi:
Design for Searching & Finding. CHI Extended Abstracts 2015: 2457-2458 - [c97]Michael J. Brzozowski, Phil Adams, Ed H. Chi:
Google+ Communities as Plazas and Topic Boards. CHI 2015: 3779-3788 - [c96]Peng Dai, Jeffrey M. Rzeszotarski, Praveen K. Paritosh, Ed H. Chi:
And Now for Something Completely Different: Improving Crowdsourcing Workflows with Micro-Diversions. CSCW 2015: 628-638 - [c95]Ed H. Chi:
Blurring of the Boundary Between Interactive Search and Recommendation. IUI 2015: 2 - [c94]Shuo Chang, Peng Dai, Jilin Chen, Ed Huai-hsin Chi:
Got Many Labels?: Deriving Topic Labels from Multiple Sources for Social Media Posts using Crowdsourcing and Ensemble Learning. WWW (Companion Volume) 2015: 397-406 - [c93]Zhe Zhao, Zhiyuan Cheng, Lichan Hong, Ed Huai-hsin Chi:
Improving User Topic Interest Profiles by Behavior Factorization. WWW 2015: 1406-1416 - 2014
- [c92]Ed H. Chi:
Location and Language Use in Social Media. LTCSS@ACL 2014: 4 - [c91]Max L. Wilson, Ed H. Chi, Stuart Reeves, David Coyle:
RepliCHI: the workshop II. CHI Extended Abstracts 2014: 33-36 - [p2]Serge Egelman, Ed H. Chi, Steven Dow:
Crowdsourcing in HCI Research. Ways of Knowing in HCI 2014: 267-289 - [p1]Daniel M. Russell, Ed H. Chi:
Looking Back: Retrospective Study Methods for HCI. Ways of Knowing in HCI 2014: 373-393 - 2013
- [j19]Alireza Sahami Shirazi, James Clawson, Yashar Hassanpour, Mohammad J. Tourian, Albrecht Schmidt, Ed H. Chi, Marko Borazio, Kristof Van Laerhoven:
Already up? using mobile phones to track & share sleep behavior. Int. J. Hum. Comput. Stud. 71(9): 878-888 (2013) - [c90]Jennifer Fernquist, Ed H. Chi:
Re-testing the Perception of Social Annotations in Web Search. RepliCHI 2013: 49-52 - [c89]Andrew Warr, Ed H. Chi:
Swipe vs. scroll: web page switching on mobile browsers. CHI 2013: 2171-2174 - [c88]Chinmay Kulkarni, Ed H. Chi:
All the news that's fit to read: a study of social annotations for news reading. CHI 2013: 2407-2416 - [c87]Max L. Wilson, Paul Resnick, David Coyle, Ed H. Chi:
RepliCHI: the workshop. CHI Extended Abstracts 2013: 3159-3162 - [c86]Chenhao Tan, Ed H. Chi, David A. Huffaker, Gueorgi Kossinets, Alexander J. Smola:
Instant foodie: predicting expert ratings from grassroots. CIKM 2013: 1127-1136 - [c85]Ed H. Chi:
The Science of Social Interactions on the Web. CW 2013: 2 - [c84]Jeffrey M. Rzeszotarski, Ed H. Chi, Praveen K. Paritosh, Peng Dai:
Inserting Micro-Breaks into Crowdsourcing Workflows. HCOMP (Works in Progress / Demos) 2013 - [c83]Ed H. Chi:
The false dichotomy between accessibility and usability. W4A 2013: 19:1-19:2 - [c82]Jennifer Fernquist, Ed H. Chi:
Perception and understanding of social annotations in web search. WWW 2013: 403-412 - [e4]Max L. Wilson, Ed H. Chi, David Coyle, Paul Resnick:
Proceedings of the CHI 2013 Workshop on the Replication of HCI Research, Paris, France, April 27-28, 2013. CEUR Workshop Proceedings 976, CEUR-WS.org 2013 [contents] - 2012
- [j18]Ed H. Chi:
Who knows?: searching for expertise on the social web: technical perspective. Commun. ACM 55(4): 110 (2012) - [j17]Daniel Reed, Ed H. Chi:
Online privacy; replicating research results. Commun. ACM 55(10): 8-9 (2012) - [j16]Ed H. Chi, Michael S. Bernstein:
Leveraging Online Populations for Crowdsourcing [Guest editors' introduction]. IEEE Internet Comput. 16(5): 10-12 (2012) - [c81]Sanjay Kairam, Mike Brzozowski, David A. Huffaker, Ed Huai-hsin Chi:
Talking in circles: selective sharing in google+. CHI 2012: 1065-1074 - [c80]Aditi S. Muralidharan, Zoltán Gyöngyi, Ed H. Chi:
Social annotations in web search. CHI 2012: 1085-1094 - [c79]Max L. Wilson, Wendy E. Mackay, Ed Huai-hsin Chi, Michael S. Bernstein, Jeffrey Nichols:
RepliCHI SIG: from a panel to a new submission venue for replication. CHI Extended Abstracts 2012: 1185-1188 - [c78]Ernesto William De Luca, Matthias Böhmer, Alan Said, Ed H. Chi:
2nd Workshop on context-awareness in retrieval and recommendation: (CaRR 2012). IUI 2012: 409-412 - [e3]Ernesto William De Luca, Matthias Böhmer, Alan Said, Ed H. Chi:
Proceedings of the 2nd Workshop on Context-awareness in Retrieval and Recommendation, CaRR '12, Lisbon, Portugal, February 14, 2012. ACM 2012, ISBN 978-1-4503-1192-2 [contents] - [e2]Joseph A. Konstan, Ed H. Chi, Kristina Höök:
CHI Conference on Human Factors in Computing Systems, CHI '12, Austin, TX, USA - May 05 - 10, 2012. ACM 2012, ISBN 978-1-4503-1015-4 [contents] - [e1]Joseph A. Konstan, Ed H. Chi, Kristina Höök:
CHI Conference on Human Factors in Computing Systems, CHI '12, Extended Abstracts Volume, Austin, TX, USA, May 5-10, 2012. ACM 2012, ISBN 978-1-4503-1016-1 [contents] - [i2]Sharoda A. Paul, Lichan Hong, Ed H. Chi:
Who is Authoritative? Understanding Reputation Mechanisms in Quora. CoRR abs/1204.3724 (2012) - 2011
- [j15]Jeannette M. Wing, Ed H. Chi:
Reviewing peer review. Commun. ACM 54(7): 10-11 (2011) - [c77]Benjamin V. Hanrahan, Guillaume Bouchard, Gregorio Convertino, Thiébaud Weksteen, Nicholas Kong, Cédric Archambeau, Ed H. Chi:
Mail2Wiki: low-cost sharing and early curation from email to wikis. C&T 2011: 98-107 - [c76]Michael S. Bernstein, Ed H. Chi, Lydia B. Chilton, Björn Hartmann, Aniket Kittur, Robert C. Miller:
Crowdsourcing and human computation: systems, studies and platforms. CHI Extended Abstracts 2011: 53-56 - [c75]Jilin Chen, Rowan Nairn, Ed Huai-hsin Chi:
Speak little and well: recommending conversations in online social streams. CHI 2011: 217-226 - [c74]Brent J. Hecht, Lichan Hong, Bongwon Suh, Ed H. Chi:
Tweets from Justin Bieber's heart: the dynamics of the location field in user profiles. CHI 2011: 237-246 - [c73]Michael S. Bernstein, Mark S. Ackerman, Ed H. Chi, Robert C. Miller:
The trouble with social computing systems research. CHI Extended Abstracts 2011: 389-398 - [c72]Max L. Wilson, Wendy E. Mackay, Ed H. Chi, Michael S. Bernstein, Daniel M. Russell, Harold W. Thimbleby:
RepliCHI - CHI should be replicating and validating results more: discuss. CHI Extended Abstracts 2011: 463-466 - [c71]Ed H. Chi, Mary Czerwinski, David R. Millen, Dave W. Randall, Gunnar Stevens, Volker Wulf, John Zimmerman:
Transferability of research findings: context-dependent or model-driven. CHI Extended Abstracts 2011: 651-654 - [c70]Dana Rotman, Sarah Vieweg, Sarita Yardi, Ed Huai-hsin Chi, Jenny Preece, Ben Shneiderman, Peter Pirolli, Tom Glaisyer:
From slacktivism to activism: participatory culture in the age of social media. CHI Extended Abstracts 2011: 819-822 - [c69]Nicholas Kong, Gregorio Convertino, Benjamin V. Hanrahan, Ed H. Chi:
VisualWikiCurator: a corporate Wiki plugin. CHI Extended Abstracts 2011: 1549-1554 - [c68]Les Nelson, Rowan Nairn, Ed H. Chi, Gregorio Convertino:
Mail2Tag: Augmenting email for sharing with implicit tag-based categorization. CTS 2011: 23-30 - [c67]Les Nelson, Gregorio Convertino, Ed H. Chi, Rowan Nairn:
Studying the Adoption of Mail2Tag: an Enterprise2.0 Tool for Sharing. ECSCW 2011: 41-60 - [c66]Lichan Hong, Gregorio Convertino, Ed H. Chi:
Language Matters In Twitter: A Large Scale Study. ICWSM 2011 - [c65]Sharoda A. Paul, Lichan Hong, Ed H. Chi:
Is Twitter a Good Place for Asking Questions? A Characterization Study. ICWSM 2011 - [c64]Nicholas Kong, Benjamin V. Hanrahan, Thiébaud Weksteen, Gregorio Convertino, Ed H. Chi:
VisualWikiCurator: human and machine intelligencefor organizing wiki content. IUI 2011: 367-370 - [c63]Benjamin V. Hanrahan, Thiébaud Weksteen, Nicholas Kong, Gregorio Convertino, Guillaume Bouchard, Cédric Archambeau, Ed H. Chi:
Mail2Wiki: posting and curating Wiki content from email. IUI 2011: 441-442 - [c62]Judd Antin, Ed H. Chi, James Howison, Sharoda A. Paul, Aaron D. Shaw, Jude Yew:
Apples to oranges?: comparing across studies of open collaboration/peer production. Int. Sym. Wikis 2011: 227-228 - 2010
- [j14]Greg Linden, Ed H. Chi, Mark Guzdial:
The chaos of the internet as an external brain; and more. Commun. ACM 53(6): 10-11 (2010) - [j13]Ed H. Chi, Ruben Ortega:
Expanding CS education; improving software development. Commun. ACM 53(9): 8-9 (2010) - [j12]Ed H. Chi, Sean Munson, Gerhard Fischer, Sarah Vieweg, Cynthia Parr:
Advancing the Design of Technology-Mediated Social Participation Systems. Computer 43(11): 29-35 (2010) - [j11]Brynn M. Evans, Ed H. Chi:
An elaborated model of social search. Inf. Process. Manag. 46(6): 656-678 (2010) - [c61]Gregorio Convertino, Sanjay Kairam, Lichan Hong, Bongwon Suh, Ed H. Chi:
Designing a cross-channel information management tool for workers in enterprise task forces. AVI 2010: 103-110 - [c60]Lichan Hong, Gregorio Convertino, Bongwon Suh, Ed H. Chi, Sanjay Kairam:
FeedWinnower: layering structures over collections of information streams. CHI 2010: 947-950 - [c59]Jilin Chen, Rowan Nairn, Les Nelson, Michael S. Bernstein, Ed H. Chi:
Short and tweet: experiments on recommending content from information streams. CHI 2010: 1185-1194 - [c58]Gregorio Convertino, Antonietta Grasso, Giorgio De Michelis, David R. Millen, Ed H. Chi:
Clorg: collective intelligence in organizations. GROUP 2010: 355-358 - [c57]Terrell Russell, Bongwon Suh, Ed H. Chi:
A Comparison of Generated Wikipedia Profiles Using Social Labeling and Automatic Keyword Extraction. ICWSM 2010 - [c56]Ed H. Chi:
Keynote: Model-Driven Research in Human-Computer Interaction. MuC 2010: 3-4 - [c55]Bongwon Suh, Lichan Hong, Peter Pirolli, Ed H. Chi:
Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network. SocialCom/PASSAT 2010: 177-184 - [c54]Michael S. Bernstein, Bongwon Suh, Lichan Hong, Jilin Chen, Sanjay Kairam, Ed H. Chi:
Eddi: interactive topic-based browsing of social status streams. UIST 2010: 303-312 - [c53]Ed H. Chi:
Model-Driven Research in Human-Centric Computing. VL/HCC 2010: 3
2000 – 2009
- 2009
- [j10]Ed H. Chi:
Information Seeking Can Be Social. Computer 42(3): 42-46 (2009) - [c52]Yvonne Kammerer, Rowan Nairn, Peter Pirolli, Ed Huai-hsin Chi:
Signpost from the masses: learning effects in an exploratory social tag search browser. CHI 2009: 625-634 - [c51]Aniket Kittur, Ed H. Chi, Bongwon Suh:
What's in Wikipedia?: mapping topics and conflict using socially annotated category structure. CHI 2009: 1509-1512 - [c50]Lichan Hong, Ed H. Chi:
Annotate once, appear anywhere: collective foraging for snippets of interest using paragraph fingerprinting. CHI 2009: 1791-1794 - [c49]Les Nelson, Christoph Held, Peter Pirolli, Lichan Hong, Diane J. Schiano, Ed H. Chi:
With a little help from my friends: examining the impact of social annotations in sensemaking tasks. CHI 2009: 1795-1798 - [c48]Gregorio Convertino, Lichan Hong, Les Nelson, Peter Pirolli, Ed H. Chi:
Activity Awareness and Social Sensemaking 2.0: Design of a Task Force Workspace. HCI (16) 2009: 128-137 - [c47]Les Nelson, Gregorio Convertino, Peter Pirolli, Lichan Hong, Ed H. Chi:
Impact on Performance and Process by a Social Annotation System: A Social Reading Experiment. HCI (16) 2009: 270-278 - [c46]Ed H. Chi:
A Position Paper on 'Living Laboratories': Rethinking Ecological Designs and Experimentation in Human-Computer Interaction. HCI (1) 2009: 597-605 - [c45]Ed H. Chi:
Augmented social cognition: using social web technology to enhance the ability of groups to remember, think, and reason. SIGMOD Conference 2009: 973-984 - [c44]Nicolas Ducheneaut, Kurt Partridge, Qingfeng Huang, Bob Price, Michael Roberts, Ed H. Chi, Victoria Bellotti, Bo Begole:
Collaborative Filtering Is Not Enough? Experiments with a Mixed-Model Recommender for Leisure Activities. UMAP 2009: 295-306 - [c43]Bongwon Suh, Gregorio Convertino, Ed H. Chi, Peter Pirolli:
The singularity is not near: slowing growth of Wikipedia. Int. Sym. Wikis 2009 - [i1]Brynn M. Evans, Ed Huai-hsin Chi:
Towards a Model of Understanding Social Search. CoRR abs/0908.0595 (2009) - 2008
- [j9]Ed H. Chi:
The Social Web: Research and Opportunities. Computer 41(9): 88-91 (2008) - [c42]Ed H. Chi, Peter Pirolli, Bongwon Suh, Aniket Kittur, Bryan A. Pendleton, Todd Mytkowicz:
Augmented Social Cognition. AAAI Spring Symposium: Social Information Processing 2008: 11-17 - [c41]Lichan Hong, Ed Huai-hsin Chi, Raluca Budiu, Peter Pirolli, Les Nelson:
SparTag.us: a low cost tagging system for foraging of web content. AVI 2008: 65-72 - [c40]Aniket Kittur, Ed H. Chi, Bongwon Suh:
Crowdsourcing user studies with Mechanical Turk. CHI 2008: 453-456 - [c39]Bongwon Suh, Ed H. Chi, Aniket Kittur, Bryan A. Pendleton:
Lifting the veil: improving accountability and social transparency in Wikipedia with wikidashboard. CHI 2008: 1037-1040 - [c38]Victoria Bellotti, James Bo Begole, Ed Huai-hsin Chi, Nicolas Ducheneaut, Ji Fang, Ellen Isaacs, Tracy Holloway King, Mark W. Newman, Kurt Partridge, Bob Price, Paul Rasmussen, Michael Roberts, Diane J. Schiano, Alan Walendowski:
Activity-based serendipitous recommendations with the Magitti mobile leisure guide. CHI 2008: 1157-1166 - [c37]Brynn M. Evans, Ed H. Chi:
Towards a model of understanding social search. SSM 2008: 83-86 - [c36]David A. Evans, Susan Feldman, Ed H. Chi, Natasa Milic-Frayling, Igor Perisic:
The social (open) workspace. CIKM 2008: 1529 - [c35]Aniket Kittur, Bongwon Suh, Ed H. Chi:
Can you ever trust a wiki?: impacting perceived trustworthiness in wikipedia. CSCW 2008: 477-480 - [c34]Brynn M. Evans, Ed H. Chi:
Towards a model of understanding social search. CSCW 2008: 485-494 - [c33]Ed H. Chi, Todd Mytkowicz:
Understanding the efficiency of social tagging systems using information theory. Hypertext 2008: 81-88 - [c32]Ed H. Chi, Todd Mytkowicz:
Understanding the Efficiency of Social Tagging Systems using Information Theory. ICWSM 2008 - 2007
- [j8]Ed Huai-hsin Chi, Lichan Hong, Julie Heiser, Stuart K. Card, Michelle Gumbrecht:
ScentIndex and ScentHighlights: productive reading techniques for conceptually reorganizing subject indexes and highlighting passages. Inf. Vis. 6(1): 32-47 (2007) - [c31]Aniket Kittur, Bongwon Suh, Bryan A. Pendleton, Ed H. Chi:
He says, she says: conflict and coordination in Wikipedia. CHI 2007: 453-462 - [c30]Ed Huai-hsin Chi, Peter Pirolli, Shyong K. Lam:
Aspects of Augmented Social Cognition: Social Information Foraging and Social Search. HCI (15) 2007: 60-69 - [c29]Ed Huai-hsin Chi, Michelle Gumbrecht, Lichan Hong:
Visual Foraging of Highlighted Text: An Eye-Tracking Study. HCI (3) 2007: 589-598 - [c28]Bongwon Suh, Ed H. Chi, Bryan A. Pendleton, Aniket Kittur:
Us vs. Them: Understanding Social Dynamics in Wikipedia with Revert Graph Visualizations. IEEE VAST 2007: 163-170 - 2006
- [c27]Eric A. Bier, Edward W. Ishak, Ed Huai-hsin Chi:
Entity quick click: rapid text copying based on automatic entity extraction. CHI Extended Abstracts 2006: 562-567 - [c26]Ed H. Chi, Lichan Hong, Julie Heiser, Stuart K. Card:
Scentindex: Conceptually Reorganizing Subject Indexes for Reading. IEEE VAST 2006: 159-166 - [c25]Eric A. Bier, Edward W. Ishak, Ed Huai-hsin Chi:
Entity Workspace: An Evidence File That Aids Memory, Inference, and Reading. ISI 2006: 466-472 - 2005
- [j7]Ed H. Chi, Gaetano Borriello, G. Hunt, Nigel Davies:
Guest Editors' Introduction: Pervasive Computing in Sports Technologies. IEEE Pervasive Comput. 4(3): 22-25 (2005) - [j6]Ed H. Chi:
Introducing wearable force sensors in martial arts. IEEE Pervasive Comput. 4(3): 47-53 (2005) - [c24]Lichan Hong, Ed Huai-hsin Chi, Stuart K. Card:
Annotating 3D electronic books. CHI Extended Abstracts 2005: 1463-1466 - [c23]Ed Huai-hsin Chi, Lichan Hong, Michelle Gumbrecht, Stuart K. Card:
ScentHighlights: highlighting conceptually-related sentences during reading. IUI 2005: 272-274 - 2004
- [c22]Stuart K. Card, Lichan Hong, Jock D. Mackinlay, Ed Huai-hsin Chi:
3Book: a 3D electronic smart book. AVI 2004: 303-307 - [c21]Stuart K. Card, Lichan Hong, Jock D. Mackinlay, Ed Huai-hsin Chi:
3Book: a scalable 3D virtual book. CHI Extended Abstracts 2004: 1095-1098 - [c20]Ed Huai-hsin Chi, Lichan Hong, Julie Heiser, Stuart K. Card:
eBooks with indexes that reorganize conceptually. CHI Extended Abstracts 2004: 1223-1226 - [c19]Ed Huai-hsin Chi, Jin Song, Greg Corbin:
"Killer App" of wearable computing: wireless force sensing body protectors for martial arts. UIST 2004: 277-285 - 2003
- [j5]Christopher Olston, Ed Huai-hsin Chi:
ScentTrails: integrating browsing and searching on the Web. Interactions 10(5): 9-10 (2003) - [j4]Chris Olston, Ed Huai-hsin Chi:
ScentTrails: Integrating browsing and searching on the Web. ACM Trans. Comput. Hum. Interact. 10(3): 177-197 (2003) - [c18]Ed Huai-hsin Chi, Adam Rosien, Gesara Supattanasiri, Amanda Williams, Christiaan Royer, Celia Chow, Erica Robles, Brinda Dalal, Julie Chen, Steve B. Cousins:
The bloodhound project: automating discovery of web usability issues using the InfoScent simulator. CHI 2003: 505-512 - 2002
- [j3]Ed Huai-hsin Chi:
Improving Web Usability Through Visualization. IEEE Internet Comput. 6(2): 64-71 (2002) - [c17]Ed H. Chi:
Expressiveness of the data flow and data state models in visualization systems. AVI 2002: 375-378 - [c16]Jeffrey Heer, Ed Huai-hsin Chi:
Separating the swarm: categorization methods for user sessions on the web. CHI 2002: 243-250 - [c15]Ed Huai-hsin Chi, Adam Rosien, Jeffrey Heer:
LumberJack: Intelligent Discovery and Analysis of Web User Traffic Composition. WEBKDD 2002: 1-16 - 2001
- [c14]Ed Huai-hsin Chi, Peter Pirolli, Kim Chen, James E. Pitkow:
Using information scent to model user information needs and actions and the Web. CHI 2001: 490-497 - 2000
- [j2]Ed H. Chi, John Riedl, Elizabeth Shoop, Phillip Barry:
Novel visualization method for biological sequence similarity reports. J. Electronic Imaging 9(4): 394-403 (2000) - [c13]Allison Woodruff, Rich Gossweiler, James E. Pitkow, Ed Huai-hsin Chi, Stuart K. Card:
Enhancing a digital book with a reading recommender. CHI 2000: 153-160 - [c12]Ed Huai-hsin Chi, Peter Pirolli, James E. Pitkow:
The scent of a site: a system for analyzing and predicting information scent, usage, and usability of a Web site. CHI 2000: 161-168 - [c11]Ed Huai-hsin Chi:
A Taxonomy of Visualization Techniques Using the Data State Reference Model. INFOVIS 2000: 69-75 - [c10]Ed H. Chi, John Riedl:
Case Study: Resource Steering in a Visualization System. VisSym 2000: 269-278
1990 – 1999
- 1999
- [c9]Ed Huai-hsin Chi:
Web Analysis Visualization Spreadsheet. WOWS 1999: 24-31 - [c8]Ed Huai-hsin Chi, Stuart K. Card:
Sensemaking of Evolving Web Sites Using Visualization Spreadsheets. INFOVIS 1999: 18-25 - 1998
- [j1]Ed Huai-hsin Chi, John Riedl, Phillip Barry, Joseph A. Konstan:
Principles for Information Visualization Spreadsheets. IEEE Computer Graphics and Applications 18(4): 30-38 (1998) - [c7]Ed Huai-hsin Chi, James E. Pitkow, Jock D. Mackinlay, Peter Pirolli, Rich Gossweiler, Stuart K. Card:
Visualizing the Evolution of Web Ecologies. CHI 1998: 400-407 - [c6]Ed Huai-hsin Chi, John Riedl:
An Operator Interaction Framework for Visualization Systems. INFOVIS 1998: 63-70 - 1997
- [c5]Ed Huai-hsin Chi, Phillip Barry, John Riedl, Joseph A. Konstan:
A spreadsheet approach to information visualization. INFOVIS 1997: 17-24 - [c4]Ed Huai-hsin Chi, Joseph A. Konstan, Phillip Barry, John Riedl:
A Spreadsheet Approach to Information Visualization. ACM Symposium on User Interface Software and Technology 1997: 79-80 - 1996
- [c3]Ed Huai-hsin Chi, John Riedl, Elizabeth Shoop, John V. Carlis, Ernest Retzel, Phillip Barry:
Flexible Information Visualization of Multivariate Data from Biological Sequence Similarity Searches. IEEE Visualization 1996: 133-140 - 1995
- [c2]Elizabeth Shoop, Ed Huai-hsin Chi, John V. Carlis, Paul Bieganski, John Riedl, Neal Dalton, Thomas Newman, Ernest Retzel:
Implementation and testing of an automated EST processing and similarity analysis system. HICSS (5) 1995: 52-61 - [c1]Ed Huai-hsin Chi, Phillip Barry, Elizabeth Shoop, John V. Carlis, Ernest Retzel, John Riedl:
Visualization of Biological Sequence Similarity Search Results. IEEE Visualization 1995: 44-51
Coauthor Index
Zhiyuan Cheng 0002
aka: Derek Zhiyuan Cheng
aka: Derek Zhiyuan Cheng
[c192] [c188] [c186] [c184] [c183] [c182] [c180] [c178] [i90] [i89] [i87] [i86] [i82] [i81] [i78] [c173] [c168] [c166] [c164] [c163] [c162] [c161] [c159] [i76] [i74] [i73] [i71] [i68] [i64] [i63] [i62] [i60] [i58] [c154] [c149] [c148] [i49] [i41] [c146] [c145] [c142] [c139] [c137] [c134] [c133] [i35] [c125] [c124] [c123] [i31] [i29] [i26] [i24] [i23] [i22] [i20] [i19] [c121] [c116] [c114] [c113] [c112] [i13] [j22] [c106] [i8] [c99] [c93] [i2] [c74] [c66] [c65] [c61] [c60] [c55] [c54] [c50] [c49] [c48] [c47] [c41] [j8] [c29] [c26] [c24] [c23] [c22] [c21] [c20]
Maheswaran Sathiamoorthy
aka: Mahesh Sathiamoorthy
aka: Mahesh Sathiamoorthy
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