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ORCIDYi Ding 0006
Person information
- affiliation: University of Chicago, IL, USA
Other persons with the same name
- Yi Ding — disambiguation page
- Yi Ding 0001
![[0000-0003-4389-5636]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-4389-5636")
— Zhejiang University, College of Electrical Engineering, Hangzhou, China (and 2 more) - Yi Ding 0002 — National Central University, Department of Electrical Engineering, Taoyuan, Taiwan
- Yi Ding 0003 — University of Electronic Science and Technology of China, School of Information and Software Engineering, Chengdu, China
- Yi Ding 0004 — Beijing University of Posts and Telecommunications, Beijing, China
- Yi Ding 0005 — Hubei University of Technology, Hubei Collaborative Innovation Center for High-Efficiency Utilization of Solar Energy, Wuhan, China
- Yi Ding 0007 — Huazhong University of Science and Technology, Department of Computer Science and Technology, Wuhan, China (and 1 more)
- Yi Ding 0008 — Shanghai Maritime University, Logistics Research Center, Shanghai, China
- Yi Ding 0009 — Beijing Wuzi University, School of Information, China
- Yi Ding 0010 — University of California Santa Barbara, Santa Barbara CA, USA
- Yi Ding 0011 — University of Texas at Dallas, TX, USA (and 1 more)
- Yi Ding 0012 — Nanyang Technological University, School of Computer Science and Engineering, Singapore
- Yi Ding 0013 — Anhui Polytechnic University, School of Economics and Management, Wuhu, China (and 1 more)
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2020 – today
- 2023
[j1]Alex Renda, Yi Ding, Michael Carbin:
Turaco: Complexity-Guided Data Sampling for Training Neural Surrogates of Programs. Proc. ACM Program. Lang. 7(OOPSLA2): 1648-1676 (2023)- [c16]Gokul Subramanian Ravi, Pranav Gokhale, Yi Ding, William M. Kirby, Kaitlin N. Smith, Jonathan M. Baker, Peter J. Love, Henry Hoffmann, Kenneth R. Brown, Frederic T. Chong:
CAFQA: A Classical Simulation Bootstrap for Variational Quantum Algorithms. ASPLOS (1) 2023: 15-29 - [c15]Jun Zhou, Qitao Shi, Yi Ding, Lin Wang, Longfei Li, Feng Zhu:
AntTune: An Efficient Distributed Hyperparameter Optimization System for Large-Scale Data. DASFAA (4) 2023: 477-489 - [c14]Meng Li, Jun Zhou, Lu Yu, Xiaoguang Huang, Yongfeng Gu, Yi Ding, Hao Ding, Longfei Li:
A Rule-based Decision System for Financial Applications. ICDE 2023: 3535-3548 - [c13]Yi Ding, Jun Zhou, Qing Cui, Lin Wang, Mengqi Zhang, Yang Dong:
DistriBayes: A Distributed Platform for Learning, Inference and Attribution on Large Scale Bayesian Network. WSDM 2023: 1184-1187 - [c12]Jun Zhou, Caizhi Tang, Qing Cui, Yi Ding, Longfei Li, Fei Wu:
DGBCT: A Scalable Distributed Gradient Boosting Causal Tree at Alipay. WWW (Companion Volume) 2023: 447-451 - [i9]Alex Renda, Yi Ding, Michael Carbin:
Turaco: Complexity-Guided Data Sampling for Training Neural Surrogates of Programs. CoRR abs/2309.11726 (2023) - 2022
- [c11]Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann:
NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction. MLSys 2022 - [i8]Gokul Subramanian Ravi, Pranav Gokhale, Yi Ding, William M. Kirby, Kaitlin N. Smith, Jonathan M. Baker, Peter J. Love, Henry Hoffmann, Kenneth R. Brown, Frederic T. Chong:
CAFQA: Clifford Ansatz For Quantum Accuracy. CoRR abs/2202.12924 (2022) - [i7]Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann:
NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction. CoRR abs/2203.08339 (2022) - [i6]Yi Ding, Alex Renda, Ahsan Pervaiz, Michael Carbin, Henry Hoffmann:
Cello: Efficient Computer Systems Optimization with Predictive Early Termination and Censored Regression. CoRR abs/2204.04831 (2022) - [i5]Hyunji Kim, Ahsan Pervaiz, Henry Hoffmann, Michael Carbin, Yi Ding:
SCOPE: Safe Exploration for Dynamic Computer Systems Optimization. CoRR abs/2204.10451 (2022) - [i4]Yi Ding, Aijia Gao, Thibaud Ryden, Kaushik Mitra, Sukumar Kalmanje, Yanai Golany, Michael Carbin, Henry Hoffmann:
Acela: Predictable Datacenter-level Maintenance Job Scheduling. CoRR abs/2212.05155 (2022) - 2021
- [c10]Alex Renda, Yi Ding, Michael Carbin:
Programming with neural surrogates of programs. Onward! 2021: 18-38 - [c9]Yi Ding, Ahsan Pervaiz, Michael Carbin, Henry Hoffmann:
Generalizable and interpretable learning for configuration extrapolation. ESEC/SIGSOFT FSE 2021: 728-740 - [i3]Alex Renda, Yi Ding, Michael Carbin:
Programming with Neural Surrogates of Programs. CoRR abs/2112.06148 (2021) - 2020
- [c8]Yi Ding, Panos Toulis:
Dynamical Systems Theory for Causal Inference with Application to Synthetic Control Methods. AISTATS 2020: 1888-1898 - [c7]Ming Gao, Yi Ding, Bryon Aragam:
A polynomial-time algorithm for learning nonparametric causal graphs. NeurIPS 2020 - [i2]Ming Gao, Yi Ding, Bryon Aragam:
A polynomial-time algorithm for learning nonparametric causal graphs. CoRR abs/2006.11970 (2020)
2010 – 2019
- 2019
- [c6]Yi Ding, Nikita Mishra, Henry Hoffmann:
Generative and multi-phase learning for computer systems optimization. ISCA 2019: 39-52 - 2017
- [c5]Yi Ding, Chenghao Liu, Peilin Zhao, Steven C. H. Hoi:
Large Scale Kernel Methods for Online AUC Maximization. ICDM 2017: 91-100 - [c4]Jun Zhou, Xiaolong Li, Peilin Zhao, Chaochao Chen, Longfei Li, Xinxing Yang, Qing Cui, Jin Yu, Xu Chen, Yi Ding, Yuan (Alan) Qi:
KunPeng: Parameter Server based Distributed Learning Systems and Its Applications in Alibaba and Ant Financial. KDD 2017: 1693-1702 - [c3]Yi Ding, Risi Kondor, Jonathan Eskreis-Winkler:
Multiresolution Kernel Approximation for Gaussian Process Regression. NIPS 2017: 3740-3748 - 2016
- [i1]Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong:
Adaptive Subgradient Methods for Online AUC Maximization. CoRR abs/1602.00351 (2016) - 2015
- [c2]Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong:
An Adaptive Gradient Method for Online AUC Maximization. AAAI 2015: 2568-2574 - 2014
- [c1]Pengcheng Wu, Yi Ding, Peilin Zhao, Chunyan Miao, Steven C. H. Hoi:
Learning Relative Similarity by Stochastic Dual Coordinate Ascent. AAAI 2014: 2142-2148
Coauthor Index
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last updated on 2024-12-13 20:06 CET by the dblp team
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