How is ChatGPT's behavior changing over time? Lingjiao Chen, Matei Zaharia, James Zou.
Arxiv, 2023. [PDF][Code and Data]
FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance. Lingjiao Chen, Matei Zaharia, James Zou.
Arxiv, 2023. [PDF][Code and Data]
Solon: Communication-efficient Byzantine-resilient Distributed Training via Redundant Gradients. Lingjiao Chen, Leshang Chen, Hongyi Wang, Susan Davidson, Edgar Dobriban.
Arxiv, 2021. [PDF]
Conference and Workshop Publications
Analyzing ChatGPT’s Behavior Shifts Over Time. Lingjiao Chen, Matei Zaharia, James Zou.
NeurIPS Conference on Neural Information Processing Systems R0-FoMo Workshop, 2023. [PDF]
DataPerf: Benchmarks for Data-centric AI Development. The DataPerf team.
NeurIPS Conference on Neural Information Processing Systems, 2023. [PDF][Website]
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions. Lingjiao Chen, Zhihua Jin, Sabri Eyuboglu, Christopher Re, Matei Zaharia, James Zou.
NeurIPS Conference on Neural Information Processing Systems, 2022. [PDF][Website]
Estimating and Explaining Model Performance When Both Covariates and Labels Shift. Lingjiao Chen, Matei Zaharia, James Zou.
NeurIPS Conference on Neural Information Processing Systems, 2022. [PDF]
Efficient Online ML API Selection for Multi-Label Classification Tasks. Lingjiao Chen, Matei Zaharia, James Zou.
ICML International Conference on Machine Learning, 2022. [PDF]
How Did the Model Change? Efficiently Assessing Machine Learning API Shifts. Lingjiao Chen, Matei Zaharia, James Zou.
ICLR International Conference on Learning Representations, 2022. [PDF]
SEAL: Interactive Tool for Semantic Error Analysis and Labeling. Nazneen Rajani, Weixin Liang, Lingjiao Chen, Meg Mitchell, James Zou.
EMNLP Conference on Empirical Methods in Natural Language Processing, 2022. [PDF]
ML API Shift Assessments: Change is Coming! Lingjiao Chen, Matei Zaharia, James Zou.
ICML International Conference on Machine Learning SRML Workshop, 2021 (Oral). [PDF]
Have the Cake and Eat It Too? Higher Accuracy and Less Expense when Using Multi-label ML APIs Online. Lingjiao Chen, Matei Zaharia, James Zou.
ICML International Conference on Machine Learning DMMLSYS Workshop, 2021. [PDF]
SOLON: Communication-efficient Byzantine-resilient Distributed Training via Redundant Gradients. Lingjiao Chen, Leshang Chen, Hongyi Wang, Susan Davidson, Edgar Dobriban.
ISCA International Symposium on Computer Architecture SPSL Workshop, 2021. [PDF]
FrugalML: How to Use ML Prediction APIs More Accurately and Cheaply. Lingjiao Chen, Matei Zaharia, James Zou.
NeurIPS Conference on Neural Information Processing Systems, 2020 (Oral). [PDF]
To Call or not to Call? Using ML Prediction APIs more Accurately and Economically. Lingjiao Chen, Matei Zaharia, James Zou.
ICML International Conference on Machine Learning EcoPaDL Workshop, 2020. [PDF]
Towards Model-based Pricing for Machine Learning in a Data Marketplace. Lingjiao Chen, Paraschos Koutris, Arun Kumar.
ACM SIGMOD International Conference on Management of Data, 2019. [PDF][Technical Report]
Demonstration of Nimbus: Model-based Pricing for Machine Learning in a Data Marketplace. Lingjiao Chen, Hongyi Wang, Leshang Chen, Paraschos Koutris, Arun Kumar.
ACM SIGMOD International Conference on Management of Data, 2019. [PDF][Code and Data]
Enabling and Optimizing Non-linear Feature Interactions in Factorized Linear Algebra. Side Li, Lingjiao Chen, Arun Kumar.
ACM SIGMOD International Conference on Management of Data, 2019. [PDF][Code and Data]
Tuple-oriented Compression for Large-scale Mini-batch Stochastic Gradient Descent. Fengan Li, Lingjiao Chen, Arun Kumar, Jeffrey F. Naughton, Jignesh M. Patel, Xi Wu.
ACM SIGMOD International Conference on Management of Data, 2019. [PDF][Technical Report][Code and Data]
The Effect of Network Width on the Performance of Large-batch Training. Lingjiao Chen, Hongyi Wang, Jinman Zhao, Dimitris Papailiopoulos, Paraschos Koutris.
NIPS Conference on Neural Information Processing Systems, 2018. [PDF][Technical Report]
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients. Lingjiao Chen, Hongyi Wang, Zachary Charles, Dimitris Papailiopoulos.
ICML International Conference on Machine Learning, 2018. [PDF][Technical Report]
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training. Xi Wu, Uyeong Jang, Jiefeng Chen, Lingjiao Chen, Somesh Jha.
ICML International Conference on Machine Learning, 2018. [PDF][Technical Report]
Draco: Robust Distributed Training against Adversaries. Lingjiao Chen, Hongyi Wang, Dimitris Papailiopoulos.
SysML, 2018. [PDF]
Accelerating Linear Algebra over Normalized Data. Lingjiao Chen.
ACM SIGMOD International Conference on Management of Data Student Research Competition, 2017. [PDF] Second Runner-up Award Winner
Model-based Pricing: Do Not Pay for More than What You Learn! Lingjiao Chen, Paraschos Koutris, Arun Kumar.
ACM SIGMOD International Conference on Management of Data DEEM Workshop, 2017. [PDF]
Journal Publications
Towards Linear Algebra over Normalized Data. Lingjiao Chen, Arun Kumar, Jeffrey F. Naughton, Jignesh M. Patel.
Proceedings of the VLDB Endowment Volume 10 Issue 11, 2017. [PDF][Technical Report][Code and Data]
Distributed User-centric Scheduling for Visible Light Communication Networks. Lingjiao Chen, Jiaheng Wang, Jiantao Zhou, Derrick Wing Kwan Ng, Robert Schober, and Chunming Zhao.
Optics Express Volume 24 Issue 14, 2016. [PDF]