Yi Ding

According to our database, Yi Ding authored at least 22 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Turaco: Complexity-Guided Data Sampling for Training Neural Surrogates of Programs.

Alex Renda, Yi Ding, Michael Carbin

Proc. ACM Program. Lang., October, 2023

DGBCT: A Scalable Distributed Gradient Boosting Causal Tree at Alipay.

Jun Zhou, Caizhi Tang, Qing Cui, Yi Ding, Longfei Li, Fei Wu

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

DistriBayes: A Distributed Platform for Learning, Inference and Attribution on Large Scale Bayesian Network.

Yi Ding, Jun Zhou, Qing Cui, Lin Wang, Mengqi Zhang, Yang Dong

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

A Rule-based Decision System for Financial Applications.

Meng Li, Jun Zhou, Lu Yu, Xiaoguang Huang, Yongfeng Gu, Yi Ding, Hao Ding, Longfei Li

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

AntTune: An Efficient Distributed Hyperparameter Optimization System for Large-Scale Data.

Jun Zhou, Qitao Shi, Yi Ding, Lin Wang, Longfei Li, Feng Zhu

Proceedings of the Database Systems for Advanced Applications, 2023

CAFQA: A Classical Simulation Bootstrap for Variational Quantum Algorithms.

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

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

2022

Acela: Predictable Datacenter-level Maintenance Job Scheduling.

Yi Ding, Aijia Gao, Thibaud Ryden, Kaushik Mitra, Sukumar Kalmanje, Yanai Golany, Michael Carbin, Henry Hoffmann

CoRR, 2022

SCOPE: Safe Exploration for Dynamic Computer Systems Optimization.

Hyunji Kim, Ahsan Pervaiz, Henry Hoffmann, Michael Carbin, Yi Ding

CoRR, 2022

Cello: Efficient Computer Systems Optimization with Predictive Early Termination and Censored Regression.

Yi Ding, Alex Renda, Ahsan Pervaiz, Michael Carbin, Henry Hoffmann

CoRR, 2022

CAFQA: Clifford Ansatz For Quantum Accuracy.

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

CoRR, 2022

NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction.

Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann

Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

2021

Generalizable and interpretable learning for configuration extrapolation.

Yi Ding, Ahsan Pervaiz, Michael Carbin, Henry Hoffmann

Proceedings of the ESEC/FSE '21: 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2021

Programming with neural surrogates of programs.

Alex Renda, Yi Ding, Michael Carbin

Proceedings of the Onward! 2021: Proceedings of the 2021 ACM SIGPLAN International Symposium on New Ideas, 2021

2020

A polynomial-time algorithm for learning nonparametric causal graphs.

Ming Gao, Yi Ding, Bryon Aragam

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Dynamical Systems Theory for Causal Inference with Application to Synthetic Control Methods.

Yi Ding, Panos Toulis

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Generative and multi-phase learning for computer systems optimization.

Yi Ding, Nikita Mishra, Henry Hoffmann

Proceedings of the 46th International Symposium on Computer Architecture, 2019

2017

Multiresolution Kernel Approximation for Gaussian Process Regression.

Yi Ding, Risi Kondor, Jonathan Eskreis-Winkler

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

KunPeng: Parameter Server based Distributed Learning Systems and Its Applications in Alibaba and Ant Financial.

Jun Zhou, Xiaolong Li, Peilin Zhao, Chaochao Chen, Longfei Li, Xinxing Yang, Qing Cui, Jin Yu, Xu Chen, Yi Ding, Yuan (Alan) Qi

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Large Scale Kernel Methods for Online AUC Maximization.

Yi Ding, Chenghao Liu, Peilin Zhao, Steven C. H. Hoi

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016

Adaptive Subgradient Methods for Online AUC Maximization.

Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong

CoRR, 2016

2015

An Adaptive Gradient Method for Online AUC Maximization.

Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Learning Relative Similarity by Stochastic Dual Coordinate Ascent.

Pengcheng Wu, Yi Ding, Peilin Zhao, Chunyan Miao, Steven C. H. Hoi

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014