Lee, Myungjin

9 publications

ICLR 2026 EXP-Bench: Can AI Conduct AI Research Experiments? Patrick Tser Jern Kon, Qiuyi Ding, Jiachen Liu, Xinyi Zhu, Jingjia Peng, Jiarong Xing, Yibo Huang, Yiming Qiu, Jayanth Srinivasa, Myungjin Lee, Mosharaf Chowdhury, Matei Zaharia, Ang Chen

ICLR 2026 KLAS: Using Similarity to Stitch Neural Networks for Improved Accuracy-Efficiency Tradeoffs Debopam Sanyal, Anantharaman S. Iyer, Alind Khare, Trisha Jain, Akshay Jajoo, Myungjin Lee, James Clayton Kerce, Alexey Tumanov

ICML 2024 A Federated Stochastic Multi-Level Compositional Minimax Algorithm for Deep AUC Maximization Xinwen Zhang, Ali Payani, Myungjin Lee, Richard Souvenir, Hongchang Gao

WACV 2024 Adaptive Deep Neural Network Inference Optimization with EENet Fatih Ilhan, Ka-Ho Chow, Sihao Hu, Tiansheng Huang, Selim Tekin, Wenqi Wei, Yanzhao Wu, Myungjin Lee, Ramana Kompella, Hugo Latapie, Gaowen Liu, Ling Liu

ECCV 2024 DεpS: Delayed Ε-Shrinking for Faster Once-for-All Training Aditya Annavajjala, Alind Khare, Animesh Agrawal, Igor Fedorov, Hugo M Latapie, Myungjin Lee, Alexey Tumanov

NeurIPS 2024 IaC-Eval: A Code Generation Benchmark for Cloud Infrastructure-as-Code Programs Patrick Tser Jern Kon, Jiachen Liu, Yiming Qiu, Weijun Fan, Ting He, Lei Lin, Haoran Zhang, Owen M. Park, George S. Elengikal, Yuxin Kang, Ang Chen, Mosharaf Chowdhury, Myungjin Lee, Xinyu Wang

TMLR 2024 Mitigating Group Bias in Federated Learning: Beyond Local Fairness Ganghua Wang, Ali Payani, Myungjin Lee, Ramana Rao Kompella

ECCV 2024 SuperFedNAS: Cost-Efficient Federated Neural Architecture Search for On-Device Inference Alind Khare, Animesh Agrawal, Aditya Annavajjala, Payman Behnam, Myungjin Lee, Hugo M Latapie, Alexey Tumanov

CVPRW 2023 Many-Task Federated Learning: A New Problem Setting and a Simple Baseline Ruisi Cai, Xiaohan Chen, Shiwei Liu, Jayanth Srinivasa, Myungjin Lee, Ramana Kompella, Zhangyang Wang