OBOE: Collaborative Filtering for AutoML Initialization. - Chengrun Yang; Yuji Akimoto; Dae Won Kim; Madeleine Udell (CoRR, 2018)

OBOE: Collaborative Filtering for AutoML Model Selection. - Chengrun Yang; Yuji Akimoto; Dae Won Kim; Madeleine Udell (KDD, 2019)

Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence. - Lijun Ding; Yingjie Fei; Qiantong Xu; Chengrun Yang (ICML, 2020)

AutoML Pipeline Selection: Efficiently Navigating the Combinatorial Space. - Chengrun Yang; Jicong Fan 001; Ziyang Wu; Madeleine Udell (KDD, 2020)

Efficient AutoML Pipeline Search with Matrix and Tensor Factorization. - Chengrun Yang; Jicong Fan 001; Ziyang Wu; Madeleine Udell (CoRR, 2020)

Low-Rank Tensor Recovery with Euclidean-Norm-Induced Schatten-p Quasi-Norm Regularization. - Jicong Fan 001; Lijun Ding; Chengrun Yang; Madeleine Udell (CoRR, 2020)

TenIPS: Inverse Propensity Sampling for Tensor Completion. - Chengrun Yang; Lijun Ding; Ziyang Wu; Madeleine Udell (AISTATS, 2021)

Multi-Objective Net Architecture Pruning for Remote Sensing Classification. - Jiaqi Zhao 001; Chengrun Yang; Yong Zhou 003; Yajie Zhou; Zhujun Jiang; Ying Chen 005 (IGARSS, 2021)

Robust Non-Linear Matrix Factorization for Dictionary Learning, Denoising, and Clustering. - Jicong Fan 001; Chengrun Yang; Madeleine Udell (IEEE Trans. Signal Process., 2021)

How Low Can We Go: Trading Memory for Error in Low-Precision Training. - Chengrun Yang; Ziyang Wu; Jerry Chee; Christopher De Sa; Madeleine Udell (ICLR, 2022)

TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets. - Chengrun Yang; Gabriel Bender; Hanxiao Liu; Pieter-Jan Kindermans; Madeleine Udell; Yifeng Lu; Quoc V. Le; Da Huang (NeurIPS, 2022)

Resource-Constrained Neural Architecture Search on Tabular Datasets. - Chengrun Yang; Gabriel Bender; Hanxiao Liu; Pieter-Jan Kindermans; Madeleine Udell; Yifeng Lu; Quoc V. Le; Da Huang (CoRR, 2022)

Euclidean-Norm-Induced Schatten-p Quasi-Norm Regularization for Low-Rank Tensor Completion and Tensor Robust Principal Component Analysis. - Jicong Fan 001; Lijun Ding; Chengrun Yang; Zhao Zhang 001; Madeleine Udell (Trans. Mach. Learn. Res., 2023)

Large Language Models as Optimizers. - Chengrun Yang; Xuezhi Wang 002; Yifeng Lu; Hanxiao Liu; Quoc V. Le; Denny Zhou; Xinyun Chen (ICLR, 2024)

CoarseUCB: A Context-Aware Bitrate Adaptation Algorithm for VBR-encoded Video Streaming. - Chengrun Yang; Gangqiang Zhou; Miao Hu 001; Qinglin Zhao; Di Wu 001 (IWCMC, 2024)

Long-form factuality in large language models. - Jerry Wei; Chengrun Yang; Xinying Song; Yifeng Lu; Nathan Hu; Jie Huang 009; Dustin Tran; Daiyi Peng; Ruibo Liu; Da Huang; Cosmo Du; Quoc V. Le (NeurIPS, 2024)

NAAM: Enhancing Automatic Task Mapping Efficiency on NUMA Machines. - Yifei Yang; Tianyufei Zhou; Linchang Xiao; Chengrun Yang; Xuezheng Liu; Miao Hu 001; Di Wu 001 (PDCAT, 2024)

Long-form factuality in large language models. - Jerry Wei; Chengrun Yang; Xinying Song; Yifeng Lu; Nathan Hu; Dustin Tran; Daiyi Peng; Ruibo Liu; Da Huang; Cosmo Du; Quoc V. Le (CoRR, 2024)

DRL-MOSHRS: A Deep Reinforcement Learning Approach for Multi-Objective Scheduling in Heterogeneous HPC Systems. - Yifei Yang; Linchang Xiao; Tianyufei Zhou; Chengrun Yang; Xuezheng Liu; Miao Hu 001 (HPSC, 2025)

TaskFlare: A Heterogeneity-aware Unified Scheduling Framework for Diverse Domain-Specific Applications in Supercomputing Environments. - Tianyufei Zhou; Yifei Yang; Chengrun Yang; Linchang Xiao; Xuezheng Liu; Miao Hu 001 (HPSC, 2025)

SETS: Leveraging Self-Verification and Self-Correction for Improved Test-Time Scaling. - Jiefeng Chen 001; Jie Ren; Xinyun Chen; Chengrun Yang; Ruoxi Sun 002; Sercan Ö. Arik (CoRR, 2025)

Dr Genre: Reinforcement Learning from Decoupled LLM Feedback for Generic Text Rewriting. - Yufei Li 001; John Nham; Ganesh Jawahar; Lei Shu; David Uthus; Yun-Hsuan Sung; Chengrun Yang; Itai Rolnick; Yi Qiao; Cong Liu 005 (CoRR, 2025)