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2020 – today
- 2024
[c71]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- [c70]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 - [c69]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 - [c68]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 - [c67]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 - [c66]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 - [c65]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 - [c64]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 - [i33]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) - [i32]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) - [i31]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) - [i30]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) - [i29]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) - [i28]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) - [i27]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
- [c63]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 - [c62]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 - [c61]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 - [c60]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 - [c59]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 - [c58]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 - [c57]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 - [c56]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 - [i26]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) - [i25]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) - [i24]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) - [i23]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) - [i22]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) - [i21]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) - [i20]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) - [i19]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) - [i18]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) - [i17]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) - 2022
- [c55]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 - [c54]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 - [c53]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 - [i16]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) - [i15]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) - 2021
- [c52]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 - [c51]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 - [c50]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 - [c49]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 - [c48]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 - [c47]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 - [c46]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 - [i14]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
- [c45]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 - [c44]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 - [c43]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 - [i13]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) - [i12]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) - [i11]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) - [i10]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) - [i9]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) - [i8]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) - [i7]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) - [i6]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)
2010 – 2019
- 2019
- [c42]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 - [c41]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 - [c40]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 - [c39]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 - [c38]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 - [i5]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) - 2018
- [j6]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) - [c37]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 - [i4]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) - 2017
- [c36]Heng-Tze Cheng, Zakaria Haque, Lichan Hong, Mustafa Ispir, Clemens Mewald, Illia Polosukhin, Georgios Roumpos, D. Sculley, Jamie Smith, David Soergel, Yuan Tang, Philipp Tucker, Martin Wicke, Cassandra Xia, Jianwei Xie:
TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks. KDD 2017: 1763-1771 - [i3]Heng-Tze Cheng, Zakaria Haque, Lichan Hong, Mustafa Ispir, Clemens Mewald, Illia Polosukhin, Georgios Roumpos, D. Sculley, Jamie Smith, David Soergel, Yuan Tang, Philipp Tucker, Martin Wicke, Cassandra Xia, Jianwei Xie:
TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks. CoRR abs/1708.02637 (2017) - 2016
- [c35]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 - [c34]Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, Rohan Anil, Zakaria Haque, Lichan Hong, Vihan Jain, Xiaobing Liu, Hemal Shah:
Wide & Deep Learning for Recommender Systems. DLRS@RecSys 2016: 7-10 - [i2]Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, Rohan Anil, Zakaria Haque, Lichan Hong, Vihan Jain, Xiaobing Liu, Hemal Shah:
Wide & Deep Learning for Recommender Systems. CoRR abs/1606.07792 (2016) - 2015
- [c33]Zhe Zhao, Zhiyuan Cheng, Lichan Hong, Ed Huai-hsin Chi:
Improving User Topic Interest Profiles by Behavior Factorization. WWW 2015: 1406-1416 - 2014
- [e2]Marina L. Gavrilova, C. J. Kenneth Tan, Xiaoyang Mao, Lichan Hong:
Transactions on Computational Science XXIII - Special Issue on Cyberworlds. Lecture Notes in Computer Science 8490, Springer 2014, ISBN 978-3-662-43789-6 [contents] - 2013
- [e1]Xiaoyang Mao, Lichan Hong:
2013 International Conference on Cyberworlds, Yokohama, Japan, October 21-23, 2013. IEEE Computer Society 2013, ISBN 978-1-4799-2245-1 [contents] - 2012
- [i1]Sharoda A. Paul, Lichan Hong, Ed H. Chi:
Who is Authoritative? Understanding Reputation Mechanisms in Quora. CoRR abs/1204.3724 (2012) - 2011
- [c32]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 - [c31]Lichan Hong, Gregorio Convertino, Ed H. Chi:
Language Matters In Twitter: A Large Scale Study. ICWSM 2011 - [c30]Sharoda A. Paul, Lichan Hong, Ed H. Chi:
Is Twitter a Good Place for Asking Questions? A Characterization Study. ICWSM 2011 - 2010
- [c29]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 - [c28]Lichan Hong, Gregorio Convertino, Bongwon Suh, Ed H. Chi, Sanjay Kairam:
FeedWinnower: layering structures over collections of information streams. CHI 2010: 947-950 - [c27]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 - [c26]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
2000 – 2009
- 2009
- [c25]Raluca Budiu, Peter Pirolli, Lichan Hong:
Remembrance of things tagged: how tagging effort affects tag production and human memory. CHI 2009: 615-624 - [c24]Lichan Hong, Ed H. Chi:
Annotate once, appear anywhere: collective foraging for snippets of interest using paragraph fingerprinting. CHI 2009: 1791-1794 - [c23]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 - [c22]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 - [c21]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 - 2008
- [c20]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 - 2007
- [j5]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) - [c19]Ed Huai-hsin Chi, Michelle Gumbrecht, Lichan Hong:
Visual Foraging of Highlighted Text: An Eye-Tracking Study. HCI (3) 2007: 589-598 - 2006
- [c18]Lichan Hong, Stuart K. Card, Jindong Chen:
Turning Pages of 3D Electronic Books. 3DUI 2006: 159-165 - [c17]Ed H. Chi, Lichan Hong, Julie Heiser, Stuart K. Card:
Scentindex: Conceptually Reorganizing Subject Indexes for Reading. IEEE VAST 2006: 159-166 - 2005
- [c16]Lichan Hong, Ed Huai-hsin Chi, Stuart K. Card:
Annotating 3D electronic books. CHI Extended Abstracts 2005: 1463-1466 - [c15]Ed Huai-hsin Chi, Lichan Hong, Michelle Gumbrecht, Stuart K. Card:
ScentHighlights: highlighting conceptually-related sentences during reading. IUI 2005: 272-274 - 2004
- [c14]Stuart K. Card, Lichan Hong, Jock D. Mackinlay, Ed Huai-hsin Chi:
3Book: a 3D electronic smart book. AVI 2004: 303-307 - [c13]Stuart K. Card, Lichan Hong, Jock D. Mackinlay, Ed Huai-hsin Chi:
3Book: a scalable 3D virtual book. CHI Extended Abstracts 2004: 1095-1098 - [c12]Ed Huai-hsin Chi, Lichan Hong, Julie Heiser, Stuart K. Card:
eBooks with indexes that reorganize conceptually. CHI Extended Abstracts 2004: 1223-1226 - 2002
- [j4]Ming Wan, Zhengrong Liang, Qi Ke, Lichan Hong, Ingmar Bitter, Arie E. Kaufman:
Automatic Centerline Extraction for Virtual Colonoscopy. IEEE Trans. Medical Imaging 21(11): 1450-1460 (2002) - 2001
- [j3]Taosong He, Lichan Hong, Dongqing Chen, Zhengrong Liang:
Reliable Path for Virtual Endoscopy: Ensuring Complete Examination of Human Organs. IEEE Trans. Vis. Comput. Graph. 7(4): 333-342 (2001)
1990 – 1999
- 1999
- [j2]Lichan Hong, Arie E. Kaufman:
Fast Projection-Based Ray-Casting Algorithm for Rendering Curvilinear Volumes. IEEE Trans. Vis. Comput. Graph. 5(4): 322-332 (1999) - 1998
- [c11]Xiaoyang Mao, Lichan Hong, Arie E. Kaufman, Noboru Fujita, Makoto Kikukawa, Atsumi Imamiya:
Multi-Granularity Noise for Curvilinear Grid LIC. Graphics Interface 1998: 193-200 - [c10]Lichan Hong, Arie E. Kaufman:
Accelerated ray-casting for curvilinear volumes. IEEE Visualization 1998: 247-253 - 1997
- [c9]Lichan Hong, Arie E. Kaufman:
Notes on Computational-space-based Ray-casting for Curvilinear Volumes. Scientific Visualization 1997: 124-129 - [c8]Lichan Hong, Shigeru Muraki, Arie E. Kaufman, Dirk Bartz, Taosong He:
Virtual voyage: interactive navigation in the human colon. SIGGRAPH 1997: 27-34 - [c7]Suya You, Lichan Hong, Ming Wan, Kittiboon Junyaprasert, Arie E. Kaufman, Shigeru Muraki, Yong Zhou, Mark Wax, Zhengrong Liang:
Interactive volume rendering for virtual colonoscopy. IEEE Visualization 1997: 433-436 - 1996
- [j1]Taosong He, Lichan Hong, Amitabh Varshney, Sidney W. Wang:
Controlled Topology Simplification. IEEE Trans. Vis. Comput. Graph. 2(2): 171-184 (1996) - [c6]Taosong He, Lichan Hong, Arie E. Kaufman, Hanspeter Pfister:
Generation of Transfer Functions with Stochastic Search Techniques. IEEE Visualization 1996: 227-234 - 1995
- [c5]Xiaoyang Mao, Lichan Hong, Arie E. Kaufman:
Splatting of Curvilinear Volumes. IEEE Visualization 1995: 61-68 - [c4]Lichan Hong, Xiaoyang Mao, Arie E. Kaufman:
Interactive Visualization of Mixed Scalar and Vector Fields. IEEE Visualization 1995: 240-247 - [c3]Taosong He, Lichan Hong, Arie E. Kaufman, Amitabh Varshney, Sidney W. Wang:
Voxel Based Object Simplification. IEEE Visualization 1995: 296-303 - 1994
- [c2]Cláudio T. Silva, Lichan Hong, Arie E. Kaufman:
Flow Surface Probes for Vector Field Visualization. Scientific Visualization 1994: 295-310 - [c1]Ricardo S. Avila, Taosong He, Lichan Hong, Arie E. Kaufman, Hanspeter Pfister, Cláudio T. Silva, Lisa M. Sobierajski, Sidney W. Wang:
VolVis: A Diversified Volume Visualization System. IEEE Visualization 1994: 31-38
Coauthor Index
Zhiyuan Cheng 0002
aka: Derek Zhiyuan Cheng
aka: Derek Zhiyuan Cheng
Ed H. Chi
aka: Ed Huai-hsin Chi
aka: Ed Huai-hsin Chi
[c71] [c70] [c69] [c68] [c67] [c66] [c65] [c64] [i33] [i32] [i31] [i30] [i29] [i28] [i27] [c63] [c62] [c61] [c60] [c59] [c58] [c57] [c56] [i26] [i25] [i24] [i23] [i22] [i21] [i20] [i19] [i18] [i17] [c55] [c54] [c53] [i16] [i15] [c52] [c51] [c50] [c49] [c48] [c47] [c46] [i14] [c45] [c44] [c43] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [c42] [c41] [c40] [c39] [c38] [i5] [j6] [c37] [i4] [c35] [c33] [i1] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [c24] [c23] [c22] [c21] [c20] [j5] [c19] [c17] [c16] [c15] [c14] [c13] [c12]
Maheswaran Sathiamoorthy
aka: Mahesh Sathiamoorthy
aka: Mahesh Sathiamoorthy
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