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Publications
Uncertainty-Aware Decarbonization for Datacenters [Slides]
Amy Li, Sihang Liu, Yi Ding
HotCarbon'24: Workshop on Sustainable Computer Systems
Towards Sustainable Large Language Model Serving [Slides]
Sophia Nguyen*, Beihao Zhou*, Yi Ding, Sihang Liu (*Equal Contributions)
HotCarbon'24: Workshop on Sustainable Computer Systems
Turaco: Complexity-Guided Data Sampling for Training Neural Surrogates of Programs
Alex Renda, Yi Ding, Michael Carbin
OOPSLA'23: The ACM SIGPLAN conference on Systems, Programming, Languages, and Applications
CAFQA: A Classical Simulation Bootstrap for Variational Quantum Algorithms
Gokul Ravi, Pranav Gokhale, Yi Ding, William Kirby, Kaitlin Smith, Peter Love, Kenneth Brown, Henry Hoffmann, Frederic Chong
ASPLOS'23: The 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems
Minimax Designs for Causal Effects in Temporal Experiments with Treatment Habituation [arXiv]
Guillaume Basse, Yi Ding, Panos Toulis
Biometrika'23 (A Top Statistics Journal)
NURD : Negative-Unlabeled Learning for Online Datacenter Straggler Prediction [Slides]
Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann
MLSys'22: The 5th Conference on Machine Learning and Systems
Programming with Neural Surrogates of Programs [Video] [Code]
Alex Renda, Yi Ding, Michael Carbin
Onward!'21: The ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software
Generalizable and Interpretable Learning for Configuration Extrapolation [Video]
Yi Ding, Ahsan Pervaiz, Michael Carbin, Henry Hoffmann
ESEC/FSE'21: The 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
Neighborhood Street Activity and Greenspace Usage Uniquely Contribute to Predicting Crime [Media]
Kathryn E Schertz, James Saxon, Carlos Cardenas-Iniguez, Luís MA Bettencourt, Yi Ding, Henry Hoffmann, Marc G Berman
npj Urban Sustainability, Nature Research Journal, 2021
A Polynomial-time Algorithm for Learning Nonparametric Causal Graphs [arXiv] [Poster] [Code]
Ming Gao, Yi Ding, Bryon Aragam
NeurIPS'20: The 34th Conference on Neural Information Processing Systems
Dynamical Systems Theory for Causal Inference with Application to Synthetic Control Methods [Video]
Yi Ding, Panos Toulis
AISTATS'20: The 23rd International Conference on Artificial Intelligence and Statistics
Generative and Multi–phase Learning for Computer Systems Optimization [Slides] [Lightning Talk] [Poster]
Yi Ding, Nikita Mishra, Henry Hoffmann
ISCA'19: The 46th International Symposium on Computer Architecture
Multiresolution Kernel Approximation for Gaussian Process Regression [arXiv] [Spotlight Video] [Poster]
Yi Ding, Risi Kondor, Jonathan Eskreis-Winkler
NeurIPS'17 (Spotlight): The 31st Conference on Neural Information Processing Systems
Large Scale Kernel Methods for Online AUC Maximization
Yi Ding, Chenghao Liu, Peilin Zhao, Steven CH Hoi
ICDM'17 (Long Oral): The IEEE International Conference on Data Mining
An Adaptive Gradient Method for Online AUC Maximization
Yi Ding, Peilin Zhao, Steven CH Hoi, Yew-Soon Ong
AAAI'15 (Oral): The 29th AAAI Conference on Artificial Intelligence
Learning Relative Similarity by Stochastic Dual Coordinate Ascent
Pengcheng Wu, Yi Ding, Peilin Zhao, Chunyan Miao, Steven CH Hoi
AAAI'14: The 28th AAAI Conference on Artificial Intelligence
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