Yi Ding - RankMe

42 papers A* 7A 2B 1Journal 21Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Cache Your Prompt When It's Green - Carbon-Aware Caching for Large Language Model Serving. Proc. ACM Meas. Anal. Comput. Syst. Yuyang Tian, Desen Sun, Yi Ding, Sihang Liu
2026	J	`jnl`	From Muscle to Text with MyoText: sEMG to Text via Finger Classification and Transformer-Based Decoding. CoRR Meghna Roy Chowdhury, Shreyas Sen, Yi Ding
2025	J	`jnl`	Disaggregated Speculative Decoding for Carbon-Efficient LLM Serving. IEEE Comput. Archit. Lett. Tianyao Shi, Yanran Wu, Sihang Liu, Yi Ding
2025	J	`jnl`	EmbAdvisor: Adaptive Cache Management for Sustainable LLM Serving. CoRR Yuyang Tian, Desen Sun, Yi Ding, Sihang Liu
2025	—	`conf`	EnsembleCI: Ensemble Learning for Carbon Intensity Forecasting. e-Energy Leyi Yan, Linda Wang, Sihang Liu, Yi Ding
2025	J	`jnl`	EnsembleCI: Ensemble Learning for Carbon Intensity Forecasting. CoRR Leyi Yan, Linda Wang, Sihang Liu, Yi Ding
2025	B	`conf`	Predicting and Understanding College Student Mental Health with Interpretable Machine Learning. CHASE Meghna Roy Chowdhury, Wei Xuan, Shreyas Sen, Yixue Zhao, Yi Ding
2025	J	`jnl`	Predicting and Understanding College Student Mental Health with Interpretable Machine Learning. CoRR Meghna Roy Chowdhury, Wei Xuan, Shreyas Sen, Yixue Zhao, Yi Ding
2025	J	`jnl`	SSL-SE-EEG: A Framework for Robust Learning from Unlabeled EEG Data with Self-Supervised Learning and Squeeze-Excitation Networks. CoRR Meghna Roy Chowdhury, Yi Ding, Shreyas Sen
2025	J	`jnl`	Towards Sustainable Large Language Model Serving. CoRR Sophia Nguyen, Beihao Zhou, Yi Ding, Sihang Liu
2025	—	`conf`	Unlocking Mental Health: Exploring College Students' Well-being through Smartphone Behaviors. MOBILESoft@ICSE Wei Xuan, Meghna Roy Chowdhury, Yi Ding, Yixue Zhao
2025	J	`jnl`	Unlocking Mental Health: Exploring College Students' Well-being through Smartphone Behaviors. CoRR Wei Xuan, Meghna Roy Chowdhury, Yi Ding, Yixue Zhao
2025	—	`conf`	Unveiling Environmental Impacts of Large Language Model Serving: A Functional Unit View. ACL (1) Yanran Wu, Inez Hua, Yi Ding
2024	J	`jnl`	GreenLLM: Disaggregating Large Language Model Serving on Heterogeneous GPUs for Lower Carbon Emissions. CoRR Tianyao Shi, Yanran Wu, Sihang Liu, Yi Ding
2024	—	`conf`	Sustainable LLM Serving: Environmental Implications, Challenges, and Opportunities : Invited Paper. IGSC Yi Ding, Tianyao Shi
2024	J	`jnl`	Uncertainty-Aware Decarbonization for Datacenters. CoRR Amy Li, Sihang Liu, Yi Ding
2023	A*	`conf`	A Rule-based Decision System for Financial Applications. ICDE Meng Li, Jun Zhou, Lu Yu, Xiaoguang Huang, Yongfeng Gu, Yi Ding, Hao Ding, Longfei Li
2023	—	`conf`	AntTune: An Efficient Distributed Hyperparameter Optimization System for Large-Scale Data. DASFAA (4) Jun Zhou, Qitao Shi, Yi Ding, Lin Wang, Longfei Li, Feng Zhu
2023	—	`conf`	CAFQA: A Classical Simulation Bootstrap for Variational Quantum Algorithms. ASPLOS (1) 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
2023	—	`conf`	DGBCT: A Scalable Distributed Gradient Boosting Causal Tree at Alipay. WWW (Companion Volume) Jun Zhou, Caizhi Tang, Qing Cui, Yi Ding, Longfei Li, Fei Wu
2023	A	`conf`	DistriBayes: A Distributed Platform for Learning, Inference and Attribution on Large Scale Bayesian Network. WSDM Yi Ding, Jun Zhou, Qing Cui, Lin Wang, Mengqi Zhang, Yang Dong
2023	J	`jnl`	Turaco: Complexity-Guided Data Sampling for Training Neural Surrogates of Programs. CoRR Alex Renda, Yi Ding, Michael Carbin
2023	J	`jnl`	Turaco: Complexity-Guided Data Sampling for Training Neural Surrogates of Programs. Proc. ACM Program. Lang. Alex Renda, Yi Ding, Michael Carbin
2022	J	`jnl`	Acela: Predictable Datacenter-level Maintenance Job Scheduling. CoRR Yi Ding, Aijia Gao, Thibaud Ryden, Kaushik Mitra, Sukumar Kalmanje, Yanai Golany, Michael Carbin, Henry Hoffmann
2022	J	`jnl`	CAFQA: Clifford Ansatz For Quantum Accuracy. CoRR 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
2022	J	`jnl`	Cello: Efficient Computer Systems Optimization with Predictive Early Termination and Censored Regression. CoRR Yi Ding, Alex Renda, Ahsan Pervaiz, Michael Carbin, Henry Hoffmann
2022	—	`conf`	NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction. MLSys Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann
2022	J	`jnl`	NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction. CoRR Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann
2022	J	`jnl`	SCOPE: Safe Exploration for Dynamic Computer Systems Optimization. CoRR Hyunji Kim, Ahsan Pervaiz, Henry Hoffmann, Michael Carbin, Yi Ding
2021	—	`conf`	Generalizable and interpretable learning for configuration extrapolation. ESEC/SIGSOFT FSE Yi Ding, Ahsan Pervaiz, Michael Carbin, Henry Hoffmann
2021	J	`jnl`	Programming with Neural Surrogates of Programs. CoRR Alex Renda, Yi Ding, Michael Carbin
2021	—	`conf`	Programming with neural surrogates of programs. Onward! Alex Renda, Yi Ding, Michael Carbin
2020	A*	`conf`	A polynomial-time algorithm for learning nonparametric causal graphs. NeurIPS Ming Gao, Yi Ding, Bryon Aragam
2020	J	`jnl`	A polynomial-time algorithm for learning nonparametric causal graphs. CoRR Ming Gao, Yi Ding, Bryon Aragam
2020	A	`conf`	Dynamical Systems Theory for Causal Inference with Application to Synthetic Control Methods. AISTATS Yi Ding, Panos Toulis
2019	A*	`conf`	Generative and multi-phase learning for computer systems optimization. ISCA Yi Ding, Nikita Mishra, Henry Hoffmann
2017	A*	`conf`	KunPeng: Parameter Server based Distributed Learning Systems and Its Applications in Alibaba and Ant Financial. KDD Jun Zhou, Xiaolong Li, Peilin Zhao, Chaochao Chen, Longfei Li, Xinxing Yang, Qing Cui, Jin Yu, Xu Chen, Yi Ding, Yuan (Alan) Qi
2017	A*	`conf`	Large Scale Kernel Methods for Online AUC Maximization. ICDM Yi Ding, Chenghao Liu, Peilin Zhao, Steven C. H. Hoi
2017	—	`conf`	Multiresolution Kernel Approximation for Gaussian Process Regression. NIPS Yi Ding, Risi Kondor, Jonathan Eskreis-Winkler
2016	J	`jnl`	Adaptive Subgradient Methods for Online AUC Maximization. CoRR Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong
2015	A*	`conf`	An Adaptive Gradient Method for Online AUC Maximization. AAAI Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong
2014	A*	`conf`	Learning Relative Similarity by Stochastic Dual Coordinate Ascent. AAAI Pengcheng Wu, Yi Ding, Peilin Zhao, Chunyan Miao, Steven C. H. Hoi