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ORCIDJingyan Wang 0001
Person information
- affiliation: Toyota Technological Institute at Chicago, IL, USA
- affiliation: Georgia Institute of Technology, School of Industrial and Systems Engineering, Atlanta, GA, USA
- affiliation (former): Carnegie Mellon University, PA, USA
Other persons with the same name
- Jingyan Wang — disambiguation page
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2020 – today
- 2025
[j1]Krishna Acharya, Juba Ziani, Jingyan Wang, Varun Vangala:
Producers Equilibria and Dynamics in Engagement-Driven Recommender Systems. Trans. Mach. Learn. Res. 2025 (2025)- [c14]Diptangshu Sen
, Jingyan Wang, Juba Ziani:
Equilibria of Data Marketplaces with Privacy-Aware Sellers under Endogenous Privacy Costs. SaTML 2025: 550-574 - [i11]Shuangning Li, Chonghuan Wang, Jingyan Wang:
Choosing the Better Bandit Algorithm under Data Sharing: When Do A/B Experiments Work? CoRR abs/2507.11891 (2025) - 2024
- [c13]Xuanzhou Chen, Austin Xu, Jingyan Wang, Ashwin Pananjady:
Learning the Eye of the Beholder: Statistical Modeling and Estimation for Personalized Color Perception. Allerton 2024: 1-8 - [i10]Krishna Acharya, Varun Vangala, Jingyan Wang, Juba Ziani:
Producers Equilibria and Dynamics in Engagement-Driven Recommender Systems. CoRR abs/2401.16641 (2024) - [i9]Diptangshu Sen, Jingyan Wang, Juba Ziani:
Equilibria of Data Marketplaces with Privacy-Aware Sellers under Endogenous Privacy Costs. CoRR abs/2402.08826 (2024) - [i8]Ilia Kuznetsov, Osama Mohammed Afzal, Koen Dercksen, Nils Dycke, Alexander Goldberg, Tom Hope, Dirk Hovy, Jonathan K. Kummerfeld, Anne Lauscher, Kevin Leyton-Brown, Sheng Lu, Mausam, Margot Mieskes, Aurélie Névéol, Danish Pruthi, Lizhen Qu, Roy Schwartz, Noah A. Smith, Thamar Solorio, Jingyan Wang, Xiaodan Zhu, Anna Rogers, Nihar B. Shah, Iryna Gurevych:
What Can Natural Language Processing Do for Peer Review? CoRR abs/2405.06563 (2024) - [i7]Iryna Gurevych, Anna Rogers, Nihar B. Shah, Jingyan Wang:
Reviewer No. 2: Old and New Problems in Peer Review (Dagstuhl Seminar 24052). Dagstuhl Reports 14(1): 130-161 (2024) - 2023
- [c12]Austin Xu, Andrew D. McRae, Jingyan Wang, Mark A. Davenport, Ashwin Pananjady:
Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning. NeurIPS 2023 - [c11]Jingyan Wang, Ashwin Pananjady:
Modeling and Correcting Bias in Sequential Evaluation. EC 2023: 1153 - [i6]Austin Xu, Andrew D. McRae, Jingyan Wang, Mark A. Davenport, Ashwin Pananjady:
Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning. CoRR abs/2309.04626 (2023) - 2022
- [b1]Jingyan Wang:
Understanding and Mitigating Biases in Evaluation. Carnegie Mellon University, USA, 2022 - [c10]Jingyan Wang, Carmel Baharav, Nihar B. Shah, Anita Williams Woolley, R. Ravi:
Allocation Schemes in Analytic Evaluation: Applicant-Centric Holistic or Attribute-Centric Segmented? HCOMP 2022: 207-218 - [c9]Gregory Kehne, Ariel D. Procaccia, Jingyan Wang:
Recruitment Strategies That Take a Chance. NeurIPS 2022 - [i5]Jingyan Wang, Ashwin Pananjady:
Modeling and Correcting Bias in Sequential Evaluation. CoRR abs/2205.01607 (2022) - [i4]Jingyan Wang, Carmel Baharav, Nihar B. Shah, Anita Williams Woolley, R. Ravi:
Allocation Schemes in Analytic Evaluation: Applicant-Centric Holistic or Attribute-Centric Segmented? CoRR abs/2209.08665 (2022) - 2021
- [c8]Jingyan Wang, Ivan Stelmakh, Yuting Wei, Nihar B. Shah:
Debiasing Evaluations That Are Biased by Evaluations. AAAI 2021: 10120-10128 - [c7]Komal Dhull, Jingyan Wang, Nihar B. Shah, Yuanzhi Li, R. Ravi:
A heuristic for statistical seriation. UAI 2021: 621-631 - 2020
- [c6]Jingyan Wang, Nihar B. Shah:
Ranking and Rating Rankings and Ratings. AAAI 2020: 13704-13707 - [c5]Jingyan Wang, Nihar B. Shah, R. Ravi:
Stretching the Effectiveness of MLE from Accuracy to Bias for Pairwise Comparisons. AISTATS 2020: 66-76 - [i3]Jingyan Wang, Ivan Stelmakh, Yuting Wei, Nihar B. Shah:
Debiasing Evaluations That are Biased by Evaluations. CoRR abs/2012.00714 (2020)
2010 – 2019
- 2019
- [c4]Jingyan Wang, Nihar B. Shah:
Your 2 is My 1, Your 3 is My 9: Handling Arbitrary Miscalibrations in Ratings. AAMAS 2019: 864-872 - [i2]Jingyan Wang, Nihar B. Shah, R. Ravi:
Stretching the Effectiveness of MLE from Accuracy to Bias for Pairwise Comparisons. CoRR abs/1906.04066 (2019) - 2018
- [c3]Jingyan Wang, Olga Russakovsky, Deva Ramanan:
The More You Look, the More You See: Towards General Object Understanding Through Recursive Refinement. WACV 2018: 1794-1803 - [i1]Jingyan Wang, Nihar B. Shah:
Your 2 is My 1, Your 3 is My 9: Handling Arbitrary Miscalibrations in Ratings. CoRR abs/1806.05085 (2018) - 2015
- [c2]K. V. Rashmi, Preetum Nakkiran, Jingyan Wang, Nihar B. Shah, Kannan Ramchandran:
Having Your Cake and Eating It Too: Jointly Optimal Erasure Codes for I/O, Storage, and Network-bandwidth. FAST 2015: 81-94 - 2014
- [c1]Steve Yadlowsky, Preetum Nakkarin, Jingyan Wang, Rishi Sharma, Laurent El Ghaoui:
Iterative Hard Thresholding for Keyword Extraction from Large Text Corpora. ICMLA 2014: 588-593
Coauthor Index
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