Gao, Ming

12 publications

NeurIPS 2024 Cross-Model Control: Improving Multiple Large Language Models in One-Time Training Jiayi Wu, Hao Sun, Hengyi Cai, Lixin Su, Shuaiqiang Wang, Dawei Yin, Xiang Li, Ming Gao

AAAI 2024 Model AI Assignments 2024 Todd W. Neller, Pia Bideau, David Bierbach, Wolfgang Hönig, Nir Lipovetzky, Christian Muise, Lino Coria, Claire Wong, Stephanie Rosenthal, Yu Lu, Ming Gao, Jingjing Zhang

AISTATS 2024 Optimal Estimation of Gaussian (poly)trees Yuhao Wang, Ming Gao, Wai Ming Tai, Bryon Aragam, Arnab Bhattacharyya

AAAI 2024 Unsupervised Gene-Cell Collective Representation Learning with Optimal Transport Jixiang Yu, Nanjun Chen, Ming Gao, Xiangtao Li, Ka-Chun Wong

ICCV 2023 DDIT: Semantic Scene Completion via Deformable Deep Implicit Templates Haoang Li, Jinhu Dong, Binghui Wen, Ming Gao, Tianyu Huang, Yun-Hui Liu, Daniel Cremers

NeurIPS 2023 DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning Kangyang Luo, Shuai Wang, Yexuan Fu, Xiang Li, Yunshi Lan, Ming Gao

CVPR 2023 GradMA: A Gradient-Memory-Based Accelerated Federated Learning with Alleviated Catastrophic Forgetting Kangyang Luo, Xiang Li, Yunshi Lan, Ming Gao

AAAI 2023 Uncertainty-Aware Self-Training for Low-Resource Neural Sequence Labeling Jianing Wang, Chengyu Wang, Jun Huang, Ming Gao, Aoying Zhou

AISTATS 2022 Optimal Estimation of Gaussian DAG Models Ming Gao, Wai Ming Tai, Bryon Aragam

NeurIPS 2021 Efficient Bayesian Network Structure Learning via Local Markov Boundary Search Ming Gao, Bryon Aragam

NeurIPS 2021 Structure Learning in Polynomial Time: Greedy Algorithms, Bregman Information, and Exponential Families Goutham Rajendran, Bohdan Kivva, Ming Gao, Bryon Aragam

NeurIPS 2020 A Polynomial-Time Algorithm for Learning Nonparametric Causal Graphs Ming Gao, Yi Ding, Bryon Aragam